specialfunctions.cs

/*************************************************************************
ALGLIB 4.01.0 (source code generated 2023-12-27)
Copyright (c) Sergey Bochkanov (ALGLIB project).

>>> SOURCE LICENSE >>>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation (www.fsf.org); either version 2 of the 
License, or (at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

A copy of the GNU General Public License is available at
http://www.fsf.org/licensing/licenses
>>> END OF LICENSE >>>
*************************************************************************/
#pragma warning disable 1691
#pragma warning disable 162
#pragma warning disable 164
#pragma warning disable 219
#pragma warning disable 8981
using System;

public partial class alglib
{

    
    /*************************************************************************
    Gamma function

    Input parameters:
        X   -   argument

    Domain:
        0 < X < 171.6
        -170 < X < 0, X is not an integer.

    Relative error:
     arithmetic   domain     # trials      peak         rms
        IEEE    -170,-33      20000       2.3e-15     3.3e-16
        IEEE     -33,  33     20000       9.4e-16     2.2e-16
        IEEE      33, 171.6   20000       2.3e-15     3.2e-16

    Cephes Math Library Release 2.8:  June, 2000
    Original copyright 1984, 1987, 1989, 1992, 2000 by Stephen L. Moshier
    Translated to AlgoPascal by Bochkanov Sergey (2005, 2006, 2007).
    *************************************************************************/
    public static double gammafunction(double x)
    {
    
        return gammafunc.gammafunction(x, null);
    }
    
    public static double gammafunction(double x, alglib.xparams _params)
    {
    
        return gammafunc.gammafunction(x, _params);
    }
    
    /*************************************************************************
    Natural logarithm of gamma function

    Input parameters:
        X       -   argument

    Result:
        logarithm of the absolute value of the Gamma(X).

    Output parameters:
        SgnGam  -   sign(Gamma(X))

    Domain:
        0 < X < 2.55e305
        -2.55e305 < X < 0, X is not an integer.

    ACCURACY:
    arithmetic      domain        # trials     peak         rms
       IEEE    0, 3                 28000     5.4e-16     1.1e-16
       IEEE    2.718, 2.556e305     40000     3.5e-16     8.3e-17
    The error criterion was relative when the function magnitude
    was greater than one but absolute when it was less than one.

    The following test used the relative error criterion, though
    at certain points the relative error could be much higher than
    indicated.
       IEEE    -200, -4             10000     4.8e-16     1.3e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1989, 1992, 2000 by Stephen L. Moshier
    Translated to AlgoPascal by Bochkanov Sergey (2005, 2006, 2007).
    *************************************************************************/
    public static double lngamma(double x, out double sgngam)
    {
        sgngam = 0;
        return gammafunc.lngamma(x, ref sgngam, null);
    }
    
    public static double lngamma(double x, out double sgngam, alglib.xparams _params)
    {
        sgngam = 0;
        return gammafunc.lngamma(x, ref sgngam, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Error function

    The integral is

                              x
                               -
                    2         | |          2
      erf(x)  =  --------     |    exp( - t  ) dt.
                 sqrt(pi)   | |
                             -
                              0

    For 0 <= |x| < 1, erf(x) = x * P4(x**2)/Q5(x**2); otherwise
    erf(x) = 1 - erfc(x).


    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE      0,1         30000       3.7e-16     1.0e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double errorfunction(double x)
    {
    
        return normaldistr.errorfunction(x, null);
    }
    
    public static double errorfunction(double x, alglib.xparams _params)
    {
    
        return normaldistr.errorfunction(x, _params);
    }
    
    /*************************************************************************
    Complementary error function

     1 - erf(x) =

                              inf.
                                -
                     2         | |          2
      erfc(x)  =  --------     |    exp( - t  ) dt
                  sqrt(pi)   | |
                              -
                               x


    For small x, erfc(x) = 1 - erf(x); otherwise rational
    approximations are computed.


    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE      0,26.6417   30000       5.7e-14     1.5e-14

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double errorfunctionc(double x)
    {
    
        return normaldistr.errorfunctionc(x, null);
    }
    
    public static double errorfunctionc(double x, alglib.xparams _params)
    {
    
        return normaldistr.errorfunctionc(x, _params);
    }
    
    /*************************************************************************
    Same as normalcdf(), obsolete name.
    *************************************************************************/
    public static double normaldistribution(double x)
    {
    
        return normaldistr.normaldistribution(x, null);
    }
    
    public static double normaldistribution(double x, alglib.xparams _params)
    {
    
        return normaldistr.normaldistribution(x, _params);
    }
    
    /*************************************************************************
    Normal distribution PDF

    Returns Gaussian probability density function:

                   1
       f(x)  = --------- * exp(-x^2/2)
               sqrt(2pi)

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double normalpdf(double x)
    {
    
        return normaldistr.normalpdf(x, null);
    }
    
    public static double normalpdf(double x, alglib.xparams _params)
    {
    
        return normaldistr.normalpdf(x, _params);
    }
    
    /*************************************************************************
    Normal distribution CDF

    Returns the area under the Gaussian probability density
    function, integrated from minus infinity to x:

                               x
                                -
                      1        | |          2
       ndtr(x)  = ---------    |    exp( - t /2 ) dt
                  sqrt(2pi)  | |
                              -
                             -inf.

                =  ( 1 + erf(z) ) / 2
                =  erfc(z) / 2

    where z = x/sqrt(2). Computation is via the functions
    erf and erfc.


    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE     -13,0        30000       3.4e-14     6.7e-15

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double normalcdf(double x)
    {
    
        return normaldistr.normalcdf(x, null);
    }
    
    public static double normalcdf(double x, alglib.xparams _params)
    {
    
        return normaldistr.normalcdf(x, _params);
    }
    
    /*************************************************************************
    Inverse of the error function

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double inverf(double e)
    {
    
        return normaldistr.inverf(e, null);
    }
    
    public static double inverf(double e, alglib.xparams _params)
    {
    
        return normaldistr.inverf(e, _params);
    }
    
    /*************************************************************************
    Same as invnormalcdf(), deprecated name
    *************************************************************************/
    public static double invnormaldistribution(double y0)
    {
    
        return normaldistr.invnormaldistribution(y0, null);
    }
    
    public static double invnormaldistribution(double y0, alglib.xparams _params)
    {
    
        return normaldistr.invnormaldistribution(y0, _params);
    }
    
    /*************************************************************************
    Inverse of Normal CDF

    Returns the argument, x, for which the area under the
    Gaussian probability density function (integrated from
    minus infinity to x) is equal to y.


    For small arguments 0 < y < exp(-2), the program computes
    z = sqrt( -2.0 * log(y) );  then the approximation is
    x = z - log(z)/z  - (1/z) P(1/z) / Q(1/z).
    There are two rational functions P/Q, one for 0 < y < exp(-32)
    and the other for y up to exp(-2).  For larger arguments,
    w = y - 0.5, and  x/sqrt(2pi) = w + w**3 R(w**2)/S(w**2)).

    ACCURACY:

                         Relative error:
    arithmetic   domain        # trials      peak         rms
       IEEE     0.125, 1        20000       7.2e-16     1.3e-16
       IEEE     3e-308, 0.135   50000       4.6e-16     9.8e-17

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double invnormalcdf(double y0)
    {
    
        return normaldistr.invnormalcdf(y0, null);
    }
    
    public static double invnormalcdf(double y0, alglib.xparams _params)
    {
    
        return normaldistr.invnormalcdf(y0, _params);
    }
    
    /*************************************************************************
    Bivariate normal PDF

    Returns probability density function of the bivariate  Gaussian  with
    correlation parameter equal to Rho:

                             1              (    x^2 - 2*rho*x*y + y^2  )
        f(x,y,rho) = ----------------- * exp( - ----------------------- )
                     2pi*sqrt(1-rho^2)      (        2*(1-rho^2)        )


    with -1<rho<+1 and arbitrary x, y.

    This function won't fail as long as Rho is in (-1,+1) range.

      -- ALGLIB --
         Copyright 15.11.2019 by Bochkanov Sergey
    *************************************************************************/
    public static double bivariatenormalpdf(double x, double y, double rho)
    {
    
        return normaldistr.bivariatenormalpdf(x, y, rho, null);
    }
    
    public static double bivariatenormalpdf(double x, double y, double rho, alglib.xparams _params)
    {
    
        return normaldistr.bivariatenormalpdf(x, y, rho, _params);
    }
    
    /*************************************************************************
    Bivariate normal CDF

    Returns the area under the bivariate Gaussian  PDF  with  correlation
    parameter equal to Rho, integrated from minus infinity to (x,y):


                                              x      y
                                              -      -
                                1            | |    | |
        bvn(x,y,rho) = -------------------   |      |   f(u,v,rho)*du*dv
                        2pi*sqrt(1-rho^2)  | |    | |
                                            -      -
                                           -INF   -INF


    where

                          (    u^2 - 2*rho*u*v + v^2  )
        f(u,v,rho)   = exp( - ----------------------- )
                          (        2*(1-rho^2)        )


    with -1<rho<+1 and arbitrary x, y.

    This subroutine uses high-precision approximation scheme proposed  by
    Alan Genz in "Numerical  Computation  of  Rectangular  Bivariate  and
    Trivariate Normal and  t  probabilities",  which  computes  CDF  with
    absolute error roughly equal to 1e-14.

    This function won't fail as long as Rho is in (-1,+1) range.

      -- ALGLIB --
         Copyright 15.11.2019 by Bochkanov Sergey
    *************************************************************************/
    public static double bivariatenormalcdf(double x, double y, double rho)
    {
    
        return normaldistr.bivariatenormalcdf(x, y, rho, null);
    }
    
    public static double bivariatenormalcdf(double x, double y, double rho, alglib.xparams _params)
    {
    
        return normaldistr.bivariatenormalcdf(x, y, rho, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Incomplete beta integral

    Returns incomplete beta integral of the arguments, evaluated
    from zero to x.  The function is defined as

                     x
        -            -
       | (a+b)      | |  a-1     b-1
     -----------    |   t   (1-t)   dt.
      -     -     | |
     | (a) | (b)   -
                    0

    The domain of definition is 0 <= x <= 1.  In this
    implementation a and b are restricted to positive values.
    The integral from x to 1 may be obtained by the symmetry
    relation

       1 - incbet( a, b, x )  =  incbet( b, a, 1-x ).

    The integral is evaluated by a continued fraction expansion
    or, when b*x is small, by a power series.

    ACCURACY:

    Tested at uniformly distributed random points (a,b,x) with a and b
    in "domain" and x between 0 and 1.
                                           Relative error
    arithmetic   domain     # trials      peak         rms
       IEEE      0,5         10000       6.9e-15     4.5e-16
       IEEE      0,85       250000       2.2e-13     1.7e-14
       IEEE      0,1000      30000       5.3e-12     6.3e-13
       IEEE      0,10000    250000       9.3e-11     7.1e-12
       IEEE      0,100000    10000       8.7e-10     4.8e-11
    Outputs smaller than the IEEE gradual underflow threshold
    were excluded from these statistics.

    Cephes Math Library, Release 2.8:  June, 2000
    Copyright 1984, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double incompletebeta(double a, double b, double x)
    {
    
        return ibetaf.incompletebeta(a, b, x, null);
    }
    
    public static double incompletebeta(double a, double b, double x, alglib.xparams _params)
    {
    
        return ibetaf.incompletebeta(a, b, x, _params);
    }
    
    /*************************************************************************
    Inverse of imcomplete beta integral

    Given y, the function finds x such that

     incbet( a, b, x ) = y .

    The routine performs interval halving or Newton iterations to find the
    root of incbet(a,b,x) - y = 0.


    ACCURACY:

                         Relative error:
                   x     a,b
    arithmetic   domain  domain  # trials    peak       rms
       IEEE      0,1    .5,10000   50000    5.8e-12   1.3e-13
       IEEE      0,1   .25,100    100000    1.8e-13   3.9e-15
       IEEE      0,1     0,5       50000    1.1e-12   5.5e-15
    With a and b constrained to half-integer or integer values:
       IEEE      0,1    .5,10000   50000    5.8e-12   1.1e-13
       IEEE      0,1    .5,100    100000    1.7e-14   7.9e-16
    With a = .5, b constrained to half-integer or integer values:
       IEEE      0,1    .5,10000   10000    8.3e-11   1.0e-11

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1996, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double invincompletebeta(double a, double b, double y)
    {
    
        return ibetaf.invincompletebeta(a, b, y, null);
    }
    
    public static double invincompletebeta(double a, double b, double y, alglib.xparams _params)
    {
    
        return ibetaf.invincompletebeta(a, b, y, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Student's t distribution

    Computes the integral from minus infinity to t of the Student
    t distribution with integer k > 0 degrees of freedom:

                                         t
                                         -
                                        | |
                 -                      |         2   -(k+1)/2
                | ( (k+1)/2 )           |  (     x   )
          ----------------------        |  ( 1 + --- )        dx
                        -               |  (      k  )
          sqrt( k pi ) | ( k/2 )        |
                                      | |
                                       -
                                      -inf.

    Relation to incomplete beta integral:

           1 - stdtr(k,t) = 0.5 * incbet( k/2, 1/2, z )
    where
           z = k/(k + t**2).

    For t < -2, this is the method of computation.  For higher t,
    a direct method is derived from integration by parts.
    Since the function is symmetric about t=0, the area under the
    right tail of the density is found by calling the function
    with -t instead of t.

    ACCURACY:

    Tested at random 1 <= k <= 25.  The "domain" refers to t.
                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE     -100,-2      50000       5.9e-15     1.4e-15
       IEEE     -2,100      500000       2.7e-15     4.9e-17

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double studenttdistribution(int k, double t)
    {
    
        return studenttdistr.studenttdistribution(k, t, null);
    }
    
    public static double studenttdistribution(int k, double t, alglib.xparams _params)
    {
    
        return studenttdistr.studenttdistribution(k, t, _params);
    }
    
    /*************************************************************************
    Functional inverse of Student's t distribution

    Given probability p, finds the argument t such that stdtr(k,t)
    is equal to p.

    ACCURACY:

    Tested at random 1 <= k <= 100.  The "domain" refers to p:
                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE    .001,.999     25000       5.7e-15     8.0e-16
       IEEE    10^-6,.001    25000       2.0e-12     2.9e-14

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double invstudenttdistribution(int k, double p)
    {
    
        return studenttdistr.invstudenttdistribution(k, p, null);
    }
    
    public static double invstudenttdistribution(int k, double p, alglib.xparams _params)
    {
    
        return studenttdistr.invstudenttdistribution(k, p, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    F distribution

    Returns the area from zero to x under the F density
    function (also known as Snedcor's density or the
    variance ratio density).  This is the density
    of x = (u1/df1)/(u2/df2), where u1 and u2 are random
    variables having Chi square distributions with df1
    and df2 degrees of freedom, respectively.
    The incomplete beta integral is used, according to the
    formula

    P(x) = incbet( df1/2, df2/2, (df1*x/(df2 + df1*x) ).


    The arguments a and b are greater than zero, and x is
    nonnegative.

    ACCURACY:

    Tested at random points (a,b,x).

                   x     a,b                     Relative error:
    arithmetic  domain  domain     # trials      peak         rms
       IEEE      0,1    0,100       100000      9.8e-15     1.7e-15
       IEEE      1,5    0,100       100000      6.5e-15     3.5e-16
       IEEE      0,1    1,10000     100000      2.2e-11     3.3e-12
       IEEE      1,5    1,10000     100000      1.1e-11     1.7e-13

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double fdistribution(int a, int b, double x)
    {
    
        return fdistr.fdistribution(a, b, x, null);
    }
    
    public static double fdistribution(int a, int b, double x, alglib.xparams _params)
    {
    
        return fdistr.fdistribution(a, b, x, _params);
    }
    
    /*************************************************************************
    Complemented F distribution

    Returns the area from x to infinity under the F density
    function (also known as Snedcor's density or the
    variance ratio density).


                         inf.
                          -
                 1       | |  a-1      b-1
    1-P(x)  =  ------    |   t    (1-t)    dt
               B(a,b)  | |
                        -
                         x


    The incomplete beta integral is used, according to the
    formula

    P(x) = incbet( df2/2, df1/2, (df2/(df2 + df1*x) ).


    ACCURACY:

    Tested at random points (a,b,x) in the indicated intervals.
                   x     a,b                     Relative error:
    arithmetic  domain  domain     # trials      peak         rms
       IEEE      0,1    1,100       100000      3.7e-14     5.9e-16
       IEEE      1,5    1,100       100000      8.0e-15     1.6e-15
       IEEE      0,1    1,10000     100000      1.8e-11     3.5e-13
       IEEE      1,5    1,10000     100000      2.0e-11     3.0e-12

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double fcdistribution(int a, int b, double x)
    {
    
        return fdistr.fcdistribution(a, b, x, null);
    }
    
    public static double fcdistribution(int a, int b, double x, alglib.xparams _params)
    {
    
        return fdistr.fcdistribution(a, b, x, _params);
    }
    
    /*************************************************************************
    Inverse of complemented F distribution

    Finds the F density argument x such that the integral
    from x to infinity of the F density is equal to the
    given probability p.

    This is accomplished using the inverse beta integral
    function and the relations

         z = incbi( df2/2, df1/2, p )
         x = df2 (1-z) / (df1 z).

    Note: the following relations hold for the inverse of
    the uncomplemented F distribution:

         z = incbi( df1/2, df2/2, p )
         x = df2 z / (df1 (1-z)).

    ACCURACY:

    Tested at random points (a,b,p).

                 a,b                     Relative error:
    arithmetic  domain     # trials      peak         rms
     For p between .001 and 1:
       IEEE     1,100       100000      8.3e-15     4.7e-16
       IEEE     1,10000     100000      2.1e-11     1.4e-13
     For p between 10^-6 and 10^-3:
       IEEE     1,100        50000      1.3e-12     8.4e-15
       IEEE     1,10000      50000      3.0e-12     4.8e-14

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double invfdistribution(int a, int b, double y)
    {
    
        return fdistr.invfdistribution(a, b, y, null);
    }
    
    public static double invfdistribution(int a, int b, double y, alglib.xparams _params)
    {
    
        return fdistr.invfdistribution(a, b, y, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Incomplete gamma integral

    The function is defined by

                              x
                               -
                      1       | |  -t  a-1
     igam(a,x)  =   -----     |   e   t   dt.
                     -      | |
                    | (a)    -
                              0


    In this implementation both arguments must be positive.
    The integral is evaluated by either a power series or
    continued fraction expansion, depending on the relative
    values of a and x.

    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE      0,30       200000       3.6e-14     2.9e-15
       IEEE      0,100      300000       9.9e-14     1.5e-14

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1985, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double incompletegamma(double a, double x)
    {
    
        return igammaf.incompletegamma(a, x, null);
    }
    
    public static double incompletegamma(double a, double x, alglib.xparams _params)
    {
    
        return igammaf.incompletegamma(a, x, _params);
    }
    
    /*************************************************************************
    Complemented incomplete gamma integral

    The function is defined by


     igamc(a,x)   =   1 - igam(a,x)

                               inf.
                                 -
                        1       | |  -t  a-1
                  =   -----     |   e   t   dt.
                       -      | |
                      | (a)    -
                                x


    In this implementation both arguments must be positive.
    The integral is evaluated by either a power series or
    continued fraction expansion, depending on the relative
    values of a and x.

    ACCURACY:

    Tested at random a, x.
                   a         x                      Relative error:
    arithmetic   domain   domain     # trials      peak         rms
       IEEE     0.5,100   0,100      200000       1.9e-14     1.7e-15
       IEEE     0.01,0.5  0,100      200000       1.4e-13     1.6e-15

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1985, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double incompletegammac(double a, double x)
    {
    
        return igammaf.incompletegammac(a, x, null);
    }
    
    public static double incompletegammac(double a, double x, alglib.xparams _params)
    {
    
        return igammaf.incompletegammac(a, x, _params);
    }
    
    /*************************************************************************
    Inverse of complemented imcomplete gamma integral

    Given p, the function finds x such that

     igamc( a, x ) = p.

    Starting with the approximate value

            3
     x = a t

     where

     t = 1 - d - ndtri(p) sqrt(d)

    and

     d = 1/9a,

    the routine performs up to 10 Newton iterations to find the
    root of igamc(a,x) - p = 0.

    ACCURACY:

    Tested at random a, p in the intervals indicated.

                   a        p                      Relative error:
    arithmetic   domain   domain     # trials      peak         rms
       IEEE     0.5,100   0,0.5       100000       1.0e-14     1.7e-15
       IEEE     0.01,0.5  0,0.5       100000       9.0e-14     3.4e-15
       IEEE    0.5,10000  0,0.5        20000       2.3e-13     3.8e-14

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double invincompletegammac(double a, double y0)
    {
    
        return igammaf.invincompletegammac(a, y0, null);
    }
    
    public static double invincompletegammac(double a, double y0, alglib.xparams _params)
    {
    
        return igammaf.invincompletegammac(a, y0, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Chi-square distribution

    Returns the area under the left hand tail (from 0 to x)
    of the Chi square probability density function with
    v degrees of freedom.


                                      x
                                       -
                           1          | |  v/2-1  -t/2
     P( x | v )   =   -----------     |   t      e     dt
                       v/2  -       | |
                      2    | (v/2)   -
                                      0

    where x is the Chi-square variable.

    The incomplete gamma integral is used, according to the
    formula

    y = chdtr( v, x ) = igam( v/2.0, x/2.0 ).

    The arguments must both be positive.

    ACCURACY:

    See incomplete gamma function


    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double chisquaredistribution(double v, double x)
    {
    
        return chisquaredistr.chisquaredistribution(v, x, null);
    }
    
    public static double chisquaredistribution(double v, double x, alglib.xparams _params)
    {
    
        return chisquaredistr.chisquaredistribution(v, x, _params);
    }
    
    /*************************************************************************
    Complemented Chi-square distribution

    Returns the area under the right hand tail (from x to
    infinity) of the Chi square probability density function
    with v degrees of freedom:

                                     inf.
                                       -
                           1          | |  v/2-1  -t/2
     P( x | v )   =   -----------     |   t      e     dt
                       v/2  -       | |
                      2    | (v/2)   -
                                      x

    where x is the Chi-square variable.

    The incomplete gamma integral is used, according to the
    formula

    y = chdtr( v, x ) = igamc( v/2.0, x/2.0 ).

    The arguments must both be positive.

    ACCURACY:

    See incomplete gamma function

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double chisquarecdistribution(double v, double x)
    {
    
        return chisquaredistr.chisquarecdistribution(v, x, null);
    }
    
    public static double chisquarecdistribution(double v, double x, alglib.xparams _params)
    {
    
        return chisquaredistr.chisquarecdistribution(v, x, _params);
    }
    
    /*************************************************************************
    Inverse of complemented Chi-square distribution

    Finds the Chi-square argument x such that the integral
    from x to infinity of the Chi-square density is equal
    to the given cumulative probability y.

    This is accomplished using the inverse gamma integral
    function and the relation

       x/2 = igami( df/2, y );

    ACCURACY:

    See inverse incomplete gamma function


    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double invchisquaredistribution(double v, double y)
    {
    
        return chisquaredistr.invchisquaredistribution(v, y, null);
    }
    
    public static double invchisquaredistribution(double v, double y, alglib.xparams _params)
    {
    
        return chisquaredistr.invchisquaredistribution(v, y, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Binomial distribution

    Returns the sum of the terms 0 through k of the Binomial
    probability density:

      k
      --  ( n )   j      n-j
      >   (   )  p  (1-p)
      --  ( j )
     j=0

    The terms are not summed directly; instead the incomplete
    beta integral is employed, according to the formula

    y = bdtr( k, n, p ) = incbet( n-k, k+1, 1-p ).

    The arguments must be positive, with p ranging from 0 to 1.

    ACCURACY:

    Tested at random points (a,b,p), with p between 0 and 1.

                  a,b                     Relative error:
    arithmetic  domain     # trials      peak         rms
     For p between 0.001 and 1:
       IEEE     0,100       100000      4.3e-15     2.6e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double binomialdistribution(int k, int n, double p)
    {
    
        return binomialdistr.binomialdistribution(k, n, p, null);
    }
    
    public static double binomialdistribution(int k, int n, double p, alglib.xparams _params)
    {
    
        return binomialdistr.binomialdistribution(k, n, p, _params);
    }
    
    /*************************************************************************
    Complemented binomial distribution

    Returns the sum of the terms k+1 through n of the Binomial
    probability density:

      n
      --  ( n )   j      n-j
      >   (   )  p  (1-p)
      --  ( j )
     j=k+1

    The terms are not summed directly; instead the incomplete
    beta integral is employed, according to the formula

    y = bdtrc( k, n, p ) = incbet( k+1, n-k, p ).

    The arguments must be positive, with p ranging from 0 to 1.

    ACCURACY:

    Tested at random points (a,b,p).

                  a,b                     Relative error:
    arithmetic  domain     # trials      peak         rms
     For p between 0.001 and 1:
       IEEE     0,100       100000      6.7e-15     8.2e-16
     For p between 0 and .001:
       IEEE     0,100       100000      1.5e-13     2.7e-15

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double binomialcdistribution(int k, int n, double p)
    {
    
        return binomialdistr.binomialcdistribution(k, n, p, null);
    }
    
    public static double binomialcdistribution(int k, int n, double p, alglib.xparams _params)
    {
    
        return binomialdistr.binomialcdistribution(k, n, p, _params);
    }
    
    /*************************************************************************
    Inverse binomial distribution

    Finds the event probability p such that the sum of the
    terms 0 through k of the Binomial probability density
    is equal to the given cumulative probability y.

    This is accomplished using the inverse beta integral
    function and the relation

    1 - p = incbi( n-k, k+1, y ).

    ACCURACY:

    Tested at random points (a,b,p).

                  a,b                     Relative error:
    arithmetic  domain     # trials      peak         rms
     For p between 0.001 and 1:
       IEEE     0,100       100000      2.3e-14     6.4e-16
       IEEE     0,10000     100000      6.6e-12     1.2e-13
     For p between 10^-6 and 0.001:
       IEEE     0,100       100000      2.0e-12     1.3e-14
       IEEE     0,10000     100000      1.5e-12     3.2e-14

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double invbinomialdistribution(int k, int n, double y)
    {
    
        return binomialdistr.invbinomialdistribution(k, n, y, null);
    }
    
    public static double invbinomialdistribution(int k, int n, double y, alglib.xparams _params)
    {
    
        return binomialdistr.invbinomialdistribution(k, n, y, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Exponential integral Ei(x)

                  x
                   -     t
                  | |   e
       Ei(x) =   -|-   ---  dt .
                | |     t
                 -
                -inf

    Not defined for x <= 0.
    See also expn.c.



    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE       0,100       50000      8.6e-16     1.3e-16

    Cephes Math Library Release 2.8:  May, 1999
    Copyright 1999 by Stephen L. Moshier
    *************************************************************************/
    public static double exponentialintegralei(double x)
    {
    
        return expintegrals.exponentialintegralei(x, null);
    }
    
    public static double exponentialintegralei(double x, alglib.xparams _params)
    {
    
        return expintegrals.exponentialintegralei(x, _params);
    }
    
    /*************************************************************************
    Exponential integral En(x)

    Evaluates the exponential integral

                    inf.
                      -
                     | |   -xt
                     |    e
         E (x)  =    |    ----  dt.
          n          |      n
                   | |     t
                    -
                     1


    Both n and x must be nonnegative.

    The routine employs either a power series, a continued
    fraction, or an asymptotic formula depending on the
    relative values of n and x.

    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE      0, 30       10000       1.7e-15     3.6e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1985, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double exponentialintegralen(double x, int n)
    {
    
        return expintegrals.exponentialintegralen(x, n, null);
    }
    
    public static double exponentialintegralen(double x, int n, alglib.xparams _params)
    {
    
        return expintegrals.exponentialintegralen(x, n, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Jacobian Elliptic Functions

    Evaluates the Jacobian elliptic functions sn(u|m), cn(u|m),
    and dn(u|m) of parameter m between 0 and 1, and real
    argument u.

    These functions are periodic, with quarter-period on the
    real axis equal to the complete elliptic integral
    ellpk(1.0-m).

    Relation to incomplete elliptic integral:
    If u = ellik(phi,m), then sn(u|m) = sin(phi),
    and cn(u|m) = cos(phi).  Phi is called the amplitude of u.

    Computation is by means of the arithmetic-geometric mean
    algorithm, except when m is within 1e-9 of 0 or 1.  In the
    latter case with m close to 1, the approximation applies
    only for phi < pi/2.

    ACCURACY:

    Tested at random points with u between 0 and 10, m between
    0 and 1.

               Absolute error (* = relative error):
    arithmetic   function   # trials      peak         rms
       IEEE      phi         10000       9.2e-16*    1.4e-16*
       IEEE      sn          50000       4.1e-15     4.6e-16
       IEEE      cn          40000       3.6e-15     4.4e-16
       IEEE      dn          10000       1.3e-12     1.8e-14

     Peak error observed in consistency check using addition
    theorem for sn(u+v) was 4e-16 (absolute).  Also tested by
    the above relation to the incomplete elliptic integral.
    Accuracy deteriorates when u is large.

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static void jacobianellipticfunctions(double u, double m, out double sn, out double cn, out double dn, out double ph)
    {
        sn = 0;
        cn = 0;
        dn = 0;
        ph = 0;
        jacobianelliptic.jacobianellipticfunctions(u, m, ref sn, ref cn, ref dn, ref ph, null);
    }
    
    public static void jacobianellipticfunctions(double u, double m, out double sn, out double cn, out double dn, out double ph, alglib.xparams _params)
    {
        sn = 0;
        cn = 0;
        dn = 0;
        ph = 0;
        jacobianelliptic.jacobianellipticfunctions(u, m, ref sn, ref cn, ref dn, ref ph, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Sine and cosine integrals

    Evaluates the integrals

                             x
                             -
                            |  cos t - 1
      Ci(x) = eul + ln x +  |  --------- dt,
                            |      t
                           -
                            0
                x
                -
               |  sin t
      Si(x) =  |  ----- dt
               |    t
              -
               0

    where eul = 0.57721566490153286061 is Euler's constant.
    The integrals are approximated by rational functions.
    For x > 8 auxiliary functions f(x) and g(x) are employed
    such that

    Ci(x) = f(x) sin(x) - g(x) cos(x)
    Si(x) = pi/2 - f(x) cos(x) - g(x) sin(x)


    ACCURACY:
       Test interval = [0,50].
    Absolute error, except relative when > 1:
    arithmetic   function   # trials      peak         rms
       IEEE        Si        30000       4.4e-16     7.3e-17
       IEEE        Ci        30000       6.9e-16     5.1e-17

    Cephes Math Library Release 2.1:  January, 1989
    Copyright 1984, 1987, 1989 by Stephen L. Moshier
    *************************************************************************/
    public static void sinecosineintegrals(double x, out double si, out double ci)
    {
        si = 0;
        ci = 0;
        trigintegrals.sinecosineintegrals(x, ref si, ref ci, null);
    }
    
    public static void sinecosineintegrals(double x, out double si, out double ci, alglib.xparams _params)
    {
        si = 0;
        ci = 0;
        trigintegrals.sinecosineintegrals(x, ref si, ref ci, _params);
    }
    
    /*************************************************************************
    Hyperbolic sine and cosine integrals

    Approximates the integrals

                               x
                               -
                              | |   cosh t - 1
      Chi(x) = eul + ln x +   |    -----------  dt,
                            | |          t
                             -
                             0

                  x
                  -
                 | |  sinh t
      Shi(x) =   |    ------  dt
               | |       t
                -
                0

    where eul = 0.57721566490153286061 is Euler's constant.
    The integrals are evaluated by power series for x < 8
    and by Chebyshev expansions for x between 8 and 88.
    For large x, both functions approach exp(x)/2x.
    Arguments greater than 88 in magnitude return MAXNUM.


    ACCURACY:

    Test interval 0 to 88.
                         Relative error:
    arithmetic   function  # trials      peak         rms
       IEEE         Shi      30000       6.9e-16     1.6e-16
           Absolute error, except relative when |Chi| > 1:
       IEEE         Chi      30000       8.4e-16     1.4e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static void hyperbolicsinecosineintegrals(double x, out double shi, out double chi)
    {
        shi = 0;
        chi = 0;
        trigintegrals.hyperbolicsinecosineintegrals(x, ref shi, ref chi, null);
    }
    
    public static void hyperbolicsinecosineintegrals(double x, out double shi, out double chi, alglib.xparams _params)
    {
        shi = 0;
        chi = 0;
        trigintegrals.hyperbolicsinecosineintegrals(x, ref shi, ref chi, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Calculation of the value of the Chebyshev polynomials of the
    first and second kinds.

    Parameters:
        r   -   polynomial kind, either 1 or 2.
        n   -   degree, n>=0
        x   -   argument, -1 <= x <= 1

    Result:
        the value of the Chebyshev polynomial at x
    *************************************************************************/
    public static double chebyshevcalculate(int r, int n, double x)
    {
    
        return chebyshev.chebyshevcalculate(r, n, x, null);
    }
    
    public static double chebyshevcalculate(int r, int n, double x, alglib.xparams _params)
    {
    
        return chebyshev.chebyshevcalculate(r, n, x, _params);
    }
    
    /*************************************************************************
    Summation of Chebyshev polynomials using Clenshaw's recurrence formula.

    This routine calculates
        c[0]*T0(x) + c[1]*T1(x) + ... + c[N]*TN(x)
    or
        c[0]*U0(x) + c[1]*U1(x) + ... + c[N]*UN(x)
    depending on the R.

    Parameters:
        r   -   polynomial kind, either 1 or 2.
        n   -   degree, n>=0
        x   -   argument

    Result:
        the value of the Chebyshev polynomial at x
    *************************************************************************/
    public static double chebyshevsum(double[] c, int r, int n, double x)
    {
    
        return chebyshev.chebyshevsum(c, r, n, x, null);
    }
    
    public static double chebyshevsum(double[] c, int r, int n, double x, alglib.xparams _params)
    {
    
        return chebyshev.chebyshevsum(c, r, n, x, _params);
    }
    
    /*************************************************************************
    Representation of Tn as C[0] + C[1]*X + ... + C[N]*X^N

    Input parameters:
        N   -   polynomial degree, n>=0

    Output parameters:
        C   -   coefficients
    *************************************************************************/
    public static void chebyshevcoefficients(int n, out double[] c)
    {
        c = new double[0];
        chebyshev.chebyshevcoefficients(n, ref c, null);
    }
    
    public static void chebyshevcoefficients(int n, out double[] c, alglib.xparams _params)
    {
        c = new double[0];
        chebyshev.chebyshevcoefficients(n, ref c, _params);
    }
    
    /*************************************************************************
    Conversion of a series of Chebyshev polynomials to a power series.

    Represents A[0]*T0(x) + A[1]*T1(x) + ... + A[N]*Tn(x) as
    B[0] + B[1]*X + ... + B[N]*X^N.

    Input parameters:
        A   -   Chebyshev series coefficients
        N   -   degree, N>=0

    Output parameters
        B   -   power series coefficients
    *************************************************************************/
    public static void fromchebyshev(double[] a, int n, out double[] b)
    {
        b = new double[0];
        chebyshev.fromchebyshev(a, n, ref b, null);
    }
    
    public static void fromchebyshev(double[] a, int n, out double[] b, alglib.xparams _params)
    {
        b = new double[0];
        chebyshev.fromchebyshev(a, n, ref b, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Poisson distribution

    Returns the sum of the first k+1 terms of the Poisson
    distribution:

      k         j
      --   -m  m
      >   e    --
      --       j!
     j=0

    The terms are not summed directly; instead the incomplete
    gamma integral is employed, according to the relation

    y = pdtr( k, m ) = igamc( k+1, m ).

    The arguments must both be positive.
    ACCURACY:

    See incomplete gamma function

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double poissondistribution(int k, double m)
    {
    
        return poissondistr.poissondistribution(k, m, null);
    }
    
    public static double poissondistribution(int k, double m, alglib.xparams _params)
    {
    
        return poissondistr.poissondistribution(k, m, _params);
    }
    
    /*************************************************************************
    Complemented Poisson distribution

    Returns the sum of the terms k+1 to infinity of the Poisson
    distribution:

     inf.       j
      --   -m  m
      >   e    --
      --       j!
     j=k+1

    The terms are not summed directly; instead the incomplete
    gamma integral is employed, according to the formula

    y = pdtrc( k, m ) = igam( k+1, m ).

    The arguments must both be positive.

    ACCURACY:

    See incomplete gamma function

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double poissoncdistribution(int k, double m)
    {
    
        return poissondistr.poissoncdistribution(k, m, null);
    }
    
    public static double poissoncdistribution(int k, double m, alglib.xparams _params)
    {
    
        return poissondistr.poissoncdistribution(k, m, _params);
    }
    
    /*************************************************************************
    Inverse Poisson distribution

    Finds the Poisson variable x such that the integral
    from 0 to x of the Poisson density is equal to the
    given probability y.

    This is accomplished using the inverse gamma integral
    function and the relation

       m = igami( k+1, y ).

    ACCURACY:

    See inverse incomplete gamma function

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double invpoissondistribution(int k, double y)
    {
    
        return poissondistr.invpoissondistribution(k, y, null);
    }
    
    public static double invpoissondistribution(int k, double y, alglib.xparams _params)
    {
    
        return poissondistr.invpoissondistribution(k, y, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Beta function


                      -     -
                     | (a) | (b)
    beta( a, b )  =  -----------.
                        -
                       | (a+b)

    For large arguments the logarithm of the function is
    evaluated using lgam(), then exponentiated.

    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE       0,30       30000       8.1e-14     1.1e-14

    Cephes Math Library Release 2.0:  April, 1987
    Copyright 1984, 1987 by Stephen L. Moshier
    *************************************************************************/
    public static double beta(double a, double b)
    {
    
        return betaf.beta(a, b, null);
    }
    
    public static double beta(double a, double b, alglib.xparams _params)
    {
    
        return betaf.beta(a, b, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Fresnel integral

    Evaluates the Fresnel integrals

              x
              -
             | |
    C(x) =   |   cos(pi/2 t**2) dt,
           | |
            -
             0

              x
              -
             | |
    S(x) =   |   sin(pi/2 t**2) dt.
           | |
            -
             0


    The integrals are evaluated by a power series for x < 1.
    For x >= 1 auxiliary functions f(x) and g(x) are employed
    such that

    C(x) = 0.5 + f(x) sin( pi/2 x**2 ) - g(x) cos( pi/2 x**2 )
    S(x) = 0.5 - f(x) cos( pi/2 x**2 ) - g(x) sin( pi/2 x**2 )



    ACCURACY:

     Relative error.

    Arithmetic  function   domain     # trials      peak         rms
      IEEE       S(x)      0, 10       10000       2.0e-15     3.2e-16
      IEEE       C(x)      0, 10       10000       1.8e-15     3.3e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static void fresnelintegral(double x, ref double c, ref double s)
    {
    
        fresnel.fresnelintegral(x, ref c, ref s, null);
    }
    
    public static void fresnelintegral(double x, ref double c, ref double s, alglib.xparams _params)
    {
    
        fresnel.fresnelintegral(x, ref c, ref s, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Psi (digamma) function

                 d      -
      psi(x)  =  -- ln | (x)
                 dx

    is the logarithmic derivative of the gamma function.
    For integer x,
                      n-1
                       -
    psi(n) = -EUL  +   >  1/k.
                       -
                      k=1

    This formula is used for 0 < n <= 10.  If x is negative, it
    is transformed to a positive argument by the reflection
    formula  psi(1-x) = psi(x) + pi cot(pi x).
    For general positive x, the argument is made greater than 10
    using the recurrence  psi(x+1) = psi(x) + 1/x.
    Then the following asymptotic expansion is applied:

                              inf.   B
                               -      2k
    psi(x) = log(x) - 1/2x -   >   -------
                               -        2k
                              k=1   2k x

    where the B2k are Bernoulli numbers.

    ACCURACY:
       Relative error (except absolute when |psi| < 1):
    arithmetic   domain     # trials      peak         rms
       IEEE      0,30        30000       1.3e-15     1.4e-16
       IEEE      -30,0       40000       1.5e-15     2.2e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1992, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double psi(double x)
    {
    
        return psif.psi(x, null);
    }
    
    public static double psi(double x, alglib.xparams _params)
    {
    
        return psif.psi(x, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Airy function

    Solution of the differential equation

    y"(x) = xy.

    The function returns the two independent solutions Ai, Bi
    and their first derivatives Ai'(x), Bi'(x).

    Evaluation is by power series summation for small x,
    by rational minimax approximations for large x.



    ACCURACY:
    Error criterion is absolute when function <= 1, relative
    when function > 1, except * denotes relative error criterion.
    For large negative x, the absolute error increases as x^1.5.
    For large positive x, the relative error increases as x^1.5.

    Arithmetic  domain   function  # trials      peak         rms
    IEEE        -10, 0     Ai        10000       1.6e-15     2.7e-16
    IEEE          0, 10    Ai        10000       2.3e-14*    1.8e-15*
    IEEE        -10, 0     Ai'       10000       4.6e-15     7.6e-16
    IEEE          0, 10    Ai'       10000       1.8e-14*    1.5e-15*
    IEEE        -10, 10    Bi        30000       4.2e-15     5.3e-16
    IEEE        -10, 10    Bi'       30000       4.9e-15     7.3e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static void airy(double x, out double ai, out double aip, out double bi, out double bip)
    {
        ai = 0;
        aip = 0;
        bi = 0;
        bip = 0;
        airyf.airy(x, ref ai, ref aip, ref bi, ref bip, null);
    }
    
    public static void airy(double x, out double ai, out double aip, out double bi, out double bip, alglib.xparams _params)
    {
        ai = 0;
        aip = 0;
        bi = 0;
        bip = 0;
        airyf.airy(x, ref ai, ref aip, ref bi, ref bip, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Dawson's Integral

    Approximates the integral

                                x
                                -
                         2     | |        2
     dawsn(x)  =  exp( -x  )   |    exp( t  ) dt
                             | |
                              -
                              0

    Three different rational approximations are employed, for
    the intervals 0 to 3.25; 3.25 to 6.25; and 6.25 up.

    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE      0,10        10000       6.9e-16     1.0e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double dawsonintegral(double x)
    {
    
        return dawson.dawsonintegral(x, null);
    }
    
    public static double dawsonintegral(double x, alglib.xparams _params)
    {
    
        return dawson.dawsonintegral(x, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Calculation of the value of the Hermite polynomial.

    Parameters:
        n   -   degree, n>=0
        x   -   argument

    Result:
        the value of the Hermite polynomial Hn at x
    *************************************************************************/
    public static double hermitecalculate(int n, double x)
    {
    
        return hermite.hermitecalculate(n, x, null);
    }
    
    public static double hermitecalculate(int n, double x, alglib.xparams _params)
    {
    
        return hermite.hermitecalculate(n, x, _params);
    }
    
    /*************************************************************************
    Summation of Hermite polynomials using Clenshaw's recurrence formula.

    This routine calculates
        c[0]*H0(x) + c[1]*H1(x) + ... + c[N]*HN(x)

    Parameters:
        n   -   degree, n>=0
        x   -   argument

    Result:
        the value of the Hermite polynomial at x
    *************************************************************************/
    public static double hermitesum(double[] c, int n, double x)
    {
    
        return hermite.hermitesum(c, n, x, null);
    }
    
    public static double hermitesum(double[] c, int n, double x, alglib.xparams _params)
    {
    
        return hermite.hermitesum(c, n, x, _params);
    }
    
    /*************************************************************************
    Representation of Hn as C[0] + C[1]*X + ... + C[N]*X^N

    Input parameters:
        N   -   polynomial degree, n>=0

    Output parameters:
        C   -   coefficients
    *************************************************************************/
    public static void hermitecoefficients(int n, out double[] c)
    {
        c = new double[0];
        hermite.hermitecoefficients(n, ref c, null);
    }
    
    public static void hermitecoefficients(int n, out double[] c, alglib.xparams _params)
    {
        c = new double[0];
        hermite.hermitecoefficients(n, ref c, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Calculation of the value of the Legendre polynomial Pn.

    Parameters:
        n   -   degree, n>=0
        x   -   argument

    Result:
        the value of the Legendre polynomial Pn at x
    *************************************************************************/
    public static double legendrecalculate(int n, double x)
    {
    
        return legendre.legendrecalculate(n, x, null);
    }
    
    public static double legendrecalculate(int n, double x, alglib.xparams _params)
    {
    
        return legendre.legendrecalculate(n, x, _params);
    }
    
    /*************************************************************************
    Summation of Legendre polynomials using Clenshaw's recurrence formula.

    This routine calculates
        c[0]*P0(x) + c[1]*P1(x) + ... + c[N]*PN(x)

    Parameters:
        n   -   degree, n>=0
        x   -   argument

    Result:
        the value of the Legendre polynomial at x
    *************************************************************************/
    public static double legendresum(double[] c, int n, double x)
    {
    
        return legendre.legendresum(c, n, x, null);
    }
    
    public static double legendresum(double[] c, int n, double x, alglib.xparams _params)
    {
    
        return legendre.legendresum(c, n, x, _params);
    }
    
    /*************************************************************************
    Representation of Pn as C[0] + C[1]*X + ... + C[N]*X^N

    Input parameters:
        N   -   polynomial degree, n>=0

    Output parameters:
        C   -   coefficients
    *************************************************************************/
    public static void legendrecoefficients(int n, out double[] c)
    {
        c = new double[0];
        legendre.legendrecoefficients(n, ref c, null);
    }
    
    public static void legendrecoefficients(int n, out double[] c, alglib.xparams _params)
    {
        c = new double[0];
        legendre.legendrecoefficients(n, ref c, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Bessel function of order zero

    Returns Bessel function of order zero of the argument.

    The domain is divided into the intervals [0, 5] and
    (5, infinity). In the first interval the following rational
    approximation is used:


           2         2
    (w - r  ) (w - r  ) P (w) / Q (w)
          1         2    3       8

               2
    where w = x  and the two r's are zeros of the function.

    In the second interval, the Hankel asymptotic expansion
    is employed with two rational functions of degree 6/6
    and 7/7.

    ACCURACY:

                         Absolute error:
    arithmetic   domain     # trials      peak         rms
       IEEE      0, 30       60000       4.2e-16     1.1e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double besselj0(double x)
    {
    
        return bessel.besselj0(x, null);
    }
    
    public static double besselj0(double x, alglib.xparams _params)
    {
    
        return bessel.besselj0(x, _params);
    }
    
    /*************************************************************************
    Bessel function of order one

    Returns Bessel function of order one of the argument.

    The domain is divided into the intervals [0, 8] and
    (8, infinity). In the first interval a 24 term Chebyshev
    expansion is used. In the second, the asymptotic
    trigonometric representation is employed using two
    rational functions of degree 5/5.

    ACCURACY:

                         Absolute error:
    arithmetic   domain      # trials      peak         rms
       IEEE      0, 30       30000       2.6e-16     1.1e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double besselj1(double x)
    {
    
        return bessel.besselj1(x, null);
    }
    
    public static double besselj1(double x, alglib.xparams _params)
    {
    
        return bessel.besselj1(x, _params);
    }
    
    /*************************************************************************
    Bessel function of integer order

    Returns Bessel function of order n, where n is a
    (possibly negative) integer.

    The ratio of jn(x) to j0(x) is computed by backward
    recurrence.  First the ratio jn/jn-1 is found by a
    continued fraction expansion.  Then the recurrence
    relating successive orders is applied until j0 or j1 is
    reached.

    If n = 0 or 1 the routine for j0 or j1 is called
    directly.

    ACCURACY:

                         Absolute error:
    arithmetic   range      # trials      peak         rms
       IEEE      0, 30        5000       4.4e-16     7.9e-17


    Not suitable for large n or x. Use jv() (fractional order) instead.

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double besseljn(int n, double x)
    {
    
        return bessel.besseljn(n, x, null);
    }
    
    public static double besseljn(int n, double x, alglib.xparams _params)
    {
    
        return bessel.besseljn(n, x, _params);
    }
    
    /*************************************************************************
    Bessel function of the second kind, order zero

    Returns Bessel function of the second kind, of order
    zero, of the argument.

    The domain is divided into the intervals [0, 5] and
    (5, infinity). In the first interval a rational approximation
    R(x) is employed to compute
      y0(x)  = R(x)  +   2 * log(x) * j0(x) / PI.
    Thus a call to j0() is required.

    In the second interval, the Hankel asymptotic expansion
    is employed with two rational functions of degree 6/6
    and 7/7.



    ACCURACY:

     Absolute error, when y0(x) < 1; else relative error:

    arithmetic   domain     # trials      peak         rms
       IEEE      0, 30       30000       1.3e-15     1.6e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double bessely0(double x)
    {
    
        return bessel.bessely0(x, null);
    }
    
    public static double bessely0(double x, alglib.xparams _params)
    {
    
        return bessel.bessely0(x, _params);
    }
    
    /*************************************************************************
    Bessel function of second kind of order one

    Returns Bessel function of the second kind of order one
    of the argument.

    The domain is divided into the intervals [0, 8] and
    (8, infinity). In the first interval a 25 term Chebyshev
    expansion is used, and a call to j1() is required.
    In the second, the asymptotic trigonometric representation
    is employed using two rational functions of degree 5/5.

    ACCURACY:

                         Absolute error:
    arithmetic   domain      # trials      peak         rms
       IEEE      0, 30       30000       1.0e-15     1.3e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double bessely1(double x)
    {
    
        return bessel.bessely1(x, null);
    }
    
    public static double bessely1(double x, alglib.xparams _params)
    {
    
        return bessel.bessely1(x, _params);
    }
    
    /*************************************************************************
    Bessel function of second kind of integer order

    Returns Bessel function of order n, where n is a
    (possibly negative) integer.

    The function is evaluated by forward recurrence on
    n, starting with values computed by the routines
    y0() and y1().

    If n = 0 or 1 the routine for y0 or y1 is called
    directly.

    ACCURACY:
                         Absolute error, except relative
                         when y > 1:
    arithmetic   domain     # trials      peak         rms
       IEEE      0, 30       30000       3.4e-15     4.3e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double besselyn(int n, double x)
    {
    
        return bessel.besselyn(n, x, null);
    }
    
    public static double besselyn(int n, double x, alglib.xparams _params)
    {
    
        return bessel.besselyn(n, x, _params);
    }
    
    /*************************************************************************
    Modified Bessel function of order zero

    Returns modified Bessel function of order zero of the
    argument.

    The function is defined as i0(x) = j0( ix ).

    The range is partitioned into the two intervals [0,8] and
    (8, infinity).  Chebyshev polynomial expansions are employed
    in each interval.

    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE      0,30        30000       5.8e-16     1.4e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double besseli0(double x)
    {
    
        return bessel.besseli0(x, null);
    }
    
    public static double besseli0(double x, alglib.xparams _params)
    {
    
        return bessel.besseli0(x, _params);
    }
    
    /*************************************************************************
    Modified Bessel function of order one

    Returns modified Bessel function of order one of the
    argument.

    The function is defined as i1(x) = -i j1( ix ).

    The range is partitioned into the two intervals [0,8] and
    (8, infinity).  Chebyshev polynomial expansions are employed
    in each interval.

    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE      0, 30       30000       1.9e-15     2.1e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1985, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double besseli1(double x)
    {
    
        return bessel.besseli1(x, null);
    }
    
    public static double besseli1(double x, alglib.xparams _params)
    {
    
        return bessel.besseli1(x, _params);
    }
    
    /*************************************************************************
    Modified Bessel function, second kind, order zero

    Returns modified Bessel function of the second kind
    of order zero of the argument.

    The range is partitioned into the two intervals [0,8] and
    (8, infinity).  Chebyshev polynomial expansions are employed
    in each interval.

    ACCURACY:

    Tested at 2000 random points between 0 and 8.  Peak absolute
    error (relative when K0 > 1) was 1.46e-14; rms, 4.26e-15.
                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE      0, 30       30000       1.2e-15     1.6e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double besselk0(double x)
    {
    
        return bessel.besselk0(x, null);
    }
    
    public static double besselk0(double x, alglib.xparams _params)
    {
    
        return bessel.besselk0(x, _params);
    }
    
    /*************************************************************************
    Modified Bessel function, second kind, order one

    Computes the modified Bessel function of the second kind
    of order one of the argument.

    The range is partitioned into the two intervals [0,2] and
    (2, infinity).  Chebyshev polynomial expansions are employed
    in each interval.

    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE      0, 30       30000       1.2e-15     1.6e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double besselk1(double x)
    {
    
        return bessel.besselk1(x, null);
    }
    
    public static double besselk1(double x, alglib.xparams _params)
    {
    
        return bessel.besselk1(x, _params);
    }
    
    /*************************************************************************
    Modified Bessel function, second kind, integer order

    Returns modified Bessel function of the second kind
    of order n of the argument.

    The range is partitioned into the two intervals [0,9.55] and
    (9.55, infinity).  An ascending power series is used in the
    low range, and an asymptotic expansion in the high range.

    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE      0,30        90000       1.8e-8      3.0e-10

    Error is high only near the crossover point x = 9.55
    between the two expansions used.

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1988, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double besselkn(int nn, double x)
    {
    
        return bessel.besselkn(nn, x, null);
    }
    
    public static double besselkn(int nn, double x, alglib.xparams _params)
    {
    
        return bessel.besselkn(nn, x, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Calculation of the value of the Laguerre polynomial.

    Parameters:
        n   -   degree, n>=0
        x   -   argument

    Result:
        the value of the Laguerre polynomial Ln at x
    *************************************************************************/
    public static double laguerrecalculate(int n, double x)
    {
    
        return laguerre.laguerrecalculate(n, x, null);
    }
    
    public static double laguerrecalculate(int n, double x, alglib.xparams _params)
    {
    
        return laguerre.laguerrecalculate(n, x, _params);
    }
    
    /*************************************************************************
    Summation of Laguerre polynomials using Clenshaw's recurrence formula.

    This routine calculates c[0]*L0(x) + c[1]*L1(x) + ... + c[N]*LN(x)

    Parameters:
        n   -   degree, n>=0
        x   -   argument

    Result:
        the value of the Laguerre polynomial at x
    *************************************************************************/
    public static double laguerresum(double[] c, int n, double x)
    {
    
        return laguerre.laguerresum(c, n, x, null);
    }
    
    public static double laguerresum(double[] c, int n, double x, alglib.xparams _params)
    {
    
        return laguerre.laguerresum(c, n, x, _params);
    }
    
    /*************************************************************************
    Representation of Ln as C[0] + C[1]*X + ... + C[N]*X^N

    Input parameters:
        N   -   polynomial degree, n>=0

    Output parameters:
        C   -   coefficients
    *************************************************************************/
    public static void laguerrecoefficients(int n, out double[] c)
    {
        c = new double[0];
        laguerre.laguerrecoefficients(n, ref c, null);
    }
    
    public static void laguerrecoefficients(int n, out double[] c, alglib.xparams _params)
    {
        c = new double[0];
        laguerre.laguerrecoefficients(n, ref c, _params);
    }

}
public partial class alglib
{

    
    /*************************************************************************
    Complete elliptic integral of the first kind

    Approximates the integral



               pi/2
                -
               | |
               |           dt
    K(m)  =    |    ------------------
               |                   2
             | |    sqrt( 1 - m sin t )
              -
               0

    using the approximation

        P(x)  -  log x Q(x).

    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE       0,1        30000       2.5e-16     6.8e-17

    Cephes Math Library, Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double ellipticintegralk(double m)
    {
    
        return elliptic.ellipticintegralk(m, null);
    }
    
    public static double ellipticintegralk(double m, alglib.xparams _params)
    {
    
        return elliptic.ellipticintegralk(m, _params);
    }
    
    /*************************************************************************
    Complete elliptic integral of the first kind

    Approximates the integral



               pi/2
                -
               | |
               |           dt
    K(m)  =    |    ------------------
               |                   2
             | |    sqrt( 1 - m sin t )
              -
               0

    where m = 1 - m1, using the approximation

        P(x)  -  log x Q(x).

    The argument m1 is used rather than m so that the logarithmic
    singularity at m = 1 will be shifted to the origin; this
    preserves maximum accuracy.

    K(0) = pi/2.

    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE       0,1        30000       2.5e-16     6.8e-17

    Cephes Math Library, Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double ellipticintegralkhighprecision(double m1)
    {
    
        return elliptic.ellipticintegralkhighprecision(m1, null);
    }
    
    public static double ellipticintegralkhighprecision(double m1, alglib.xparams _params)
    {
    
        return elliptic.ellipticintegralkhighprecision(m1, _params);
    }
    
    /*************************************************************************
    Incomplete elliptic integral of the first kind F(phi|m)

    Approximates the integral



                   phi
                    -
                   | |
                   |           dt
    F(phi_\m)  =    |    ------------------
                   |                   2
                 | |    sqrt( 1 - m sin t )
                  -
                   0

    of amplitude phi and modulus m, using the arithmetic -
    geometric mean algorithm.




    ACCURACY:

    Tested at random points with m in [0, 1] and phi as indicated.

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE     -10,10       200000      7.4e-16     1.0e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double incompleteellipticintegralk(double phi, double m)
    {
    
        return elliptic.incompleteellipticintegralk(phi, m, null);
    }
    
    public static double incompleteellipticintegralk(double phi, double m, alglib.xparams _params)
    {
    
        return elliptic.incompleteellipticintegralk(phi, m, _params);
    }
    
    /*************************************************************************
    Complete elliptic integral of the second kind

    Approximates the integral


               pi/2
                -
               | |                 2
    E(m)  =    |    sqrt( 1 - m sin t ) dt
             | |
              -
               0

    using the approximation

         P(x)  -  x log x Q(x).

    ACCURACY:

                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE       0, 1       10000       2.1e-16     7.3e-17

    Cephes Math Library, Release 2.8: June, 2000
    Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double ellipticintegrale(double m)
    {
    
        return elliptic.ellipticintegrale(m, null);
    }
    
    public static double ellipticintegrale(double m, alglib.xparams _params)
    {
    
        return elliptic.ellipticintegrale(m, _params);
    }
    
    /*************************************************************************
    Incomplete elliptic integral of the second kind

    Approximates the integral


                   phi
                    -
                   | |
                   |                   2
    E(phi_\m)  =    |    sqrt( 1 - m sin t ) dt
                   |
                 | |
                  -
                   0

    of amplitude phi and modulus m, using the arithmetic -
    geometric mean algorithm.

    ACCURACY:

    Tested at random arguments with phi in [-10, 10] and m in
    [0, 1].
                         Relative error:
    arithmetic   domain     # trials      peak         rms
       IEEE     -10,10      150000       3.3e-15     1.4e-16

    Cephes Math Library Release 2.8:  June, 2000
    Copyright 1984, 1987, 1993, 2000 by Stephen L. Moshier
    *************************************************************************/
    public static double incompleteellipticintegrale(double phi, double m)
    {
    
        return elliptic.incompleteellipticintegrale(phi, m, null);
    }
    
    public static double incompleteellipticintegrale(double phi, double m, alglib.xparams _params)
    {
    
        return elliptic.incompleteellipticintegrale(phi, m, _params);
    }

}
public partial class alglib
{
    public class gammafunc
    {
        /*************************************************************************
        Gamma function

        Input parameters:
            X   -   argument

        Domain:
            0 < X < 171.6
            -170 < X < 0, X is not an integer.

        Relative error:
         arithmetic   domain     # trials      peak         rms
            IEEE    -170,-33      20000       2.3e-15     3.3e-16
            IEEE     -33,  33     20000       9.4e-16     2.2e-16
            IEEE      33, 171.6   20000       2.3e-15     3.2e-16

        Cephes Math Library Release 2.8:  June, 2000
        Original copyright 1984, 1987, 1989, 1992, 2000 by Stephen L. Moshier
        Translated to AlgoPascal by Bochkanov Sergey (2005, 2006, 2007).
        *************************************************************************/
        public static double gammafunction(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double p = 0;
            double pp = 0;
            double q = 0;
            double qq = 0;
            double z = 0;
            int i = 0;
            double sgngam = 0;

            sgngam = 1;
            q = Math.Abs(x);
            if( (double)(q)>(double)(33.0) )
            {
                if( (double)(x)<(double)(0.0) )
                {
                    p = (int)Math.Floor(q);
                    i = (int)Math.Round(p);
                    if( i%2==0 )
                    {
                        sgngam = -1;
                    }
                    z = q-p;
                    if( (double)(z)>(double)(0.5) )
                    {
                        p = p+1;
                        z = q-p;
                    }
                    z = q*Math.Sin(Math.PI*z);
                    z = Math.Abs(z);
                    z = Math.PI/(z*gammastirf(q, _params));
                }
                else
                {
                    z = gammastirf(x, _params);
                }
                result = sgngam*z;
                return result;
            }
            z = 1;
            while( (double)(x)>=(double)(3) )
            {
                x = x-1;
                z = z*x;
            }
            while( (double)(x)<(double)(0) )
            {
                if( (double)(x)>(double)(-0.000000001) )
                {
                    result = z/((1+0.5772156649015329*x)*x);
                    return result;
                }
                z = z/x;
                x = x+1;
            }
            while( (double)(x)<(double)(2) )
            {
                if( (double)(x)<(double)(0.000000001) )
                {
                    result = z/((1+0.5772156649015329*x)*x);
                    return result;
                }
                z = z/x;
                x = x+1.0;
            }
            if( (double)(x)==(double)(2) )
            {
                result = z;
                return result;
            }
            x = x-2.0;
            pp = 1.60119522476751861407E-4;
            pp = 1.19135147006586384913E-3+x*pp;
            pp = 1.04213797561761569935E-2+x*pp;
            pp = 4.76367800457137231464E-2+x*pp;
            pp = 2.07448227648435975150E-1+x*pp;
            pp = 4.94214826801497100753E-1+x*pp;
            pp = 9.99999999999999996796E-1+x*pp;
            qq = -2.31581873324120129819E-5;
            qq = 5.39605580493303397842E-4+x*qq;
            qq = -4.45641913851797240494E-3+x*qq;
            qq = 1.18139785222060435552E-2+x*qq;
            qq = 3.58236398605498653373E-2+x*qq;
            qq = -2.34591795718243348568E-1+x*qq;
            qq = 7.14304917030273074085E-2+x*qq;
            qq = 1.00000000000000000320+x*qq;
            result = z*pp/qq;
            return result;
        }


        /*************************************************************************
        Natural logarithm of gamma function

        Input parameters:
            X       -   argument

        Result:
            logarithm of the absolute value of the Gamma(X).

        Output parameters:
            SgnGam  -   sign(Gamma(X))

        Domain:
            0 < X < 2.55e305
            -2.55e305 < X < 0, X is not an integer.

        ACCURACY:
        arithmetic      domain        # trials     peak         rms
           IEEE    0, 3                 28000     5.4e-16     1.1e-16
           IEEE    2.718, 2.556e305     40000     3.5e-16     8.3e-17
        The error criterion was relative when the function magnitude
        was greater than one but absolute when it was less than one.

        The following test used the relative error criterion, though
        at certain points the relative error could be much higher than
        indicated.
           IEEE    -200, -4             10000     4.8e-16     1.3e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1989, 1992, 2000 by Stephen L. Moshier
        Translated to AlgoPascal by Bochkanov Sergey (2005, 2006, 2007).
        *************************************************************************/
        public static double lngamma(double x,
            ref double sgngam,
            alglib.xparams _params)
        {
            double result = 0;
            double a = 0;
            double b = 0;
            double c = 0;
            double p = 0;
            double q = 0;
            double u = 0;
            double w = 0;
            double z = 0;
            int i = 0;
            double logpi = 0;
            double ls2pi = 0;
            double tmp = 0;

            sgngam = 0;

            sgngam = 1;
            logpi = 1.14472988584940017414;
            ls2pi = 0.91893853320467274178;
            if( (double)(x)<(double)(-34.0) )
            {
                q = -x;
                w = lngamma(q, ref tmp, _params);
                p = (int)Math.Floor(q);
                i = (int)Math.Round(p);
                if( i%2==0 )
                {
                    sgngam = -1;
                }
                else
                {
                    sgngam = 1;
                }
                z = q-p;
                if( (double)(z)>(double)(0.5) )
                {
                    p = p+1;
                    z = p-q;
                }
                z = q*Math.Sin(Math.PI*z);
                result = logpi-Math.Log(z)-w;
                return result;
            }
            if( (double)(x)<(double)(13) )
            {
                z = 1;
                p = 0;
                u = x;
                while( (double)(u)>=(double)(3) )
                {
                    p = p-1;
                    u = x+p;
                    z = z*u;
                }
                while( (double)(u)<(double)(2) )
                {
                    z = z/u;
                    p = p+1;
                    u = x+p;
                }
                if( (double)(z)<(double)(0) )
                {
                    sgngam = -1;
                    z = -z;
                }
                else
                {
                    sgngam = 1;
                }
                if( (double)(u)==(double)(2) )
                {
                    result = Math.Log(z);
                    return result;
                }
                p = p-2;
                x = x+p;
                b = -1378.25152569120859100;
                b = -38801.6315134637840924+x*b;
                b = -331612.992738871184744+x*b;
                b = -1162370.97492762307383+x*b;
                b = -1721737.00820839662146+x*b;
                b = -853555.664245765465627+x*b;
                c = 1;
                c = -351.815701436523470549+x*c;
                c = -17064.2106651881159223+x*c;
                c = -220528.590553854454839+x*c;
                c = -1139334.44367982507207+x*c;
                c = -2532523.07177582951285+x*c;
                c = -2018891.41433532773231+x*c;
                p = x*b/c;
                result = Math.Log(z)+p;
                return result;
            }
            q = (x-0.5)*Math.Log(x)-x+ls2pi;
            if( (double)(x)>(double)(100000000) )
            {
                result = q;
                return result;
            }
            p = 1/(x*x);
            if( (double)(x)>=(double)(1000.0) )
            {
                q = q+((7.9365079365079365079365*0.0001*p-2.7777777777777777777778*0.001)*p+0.0833333333333333333333)/x;
            }
            else
            {
                a = 8.11614167470508450300*0.0001;
                a = -(5.95061904284301438324*0.0001)+p*a;
                a = 7.93650340457716943945*0.0001+p*a;
                a = -(2.77777777730099687205*0.001)+p*a;
                a = 8.33333333333331927722*0.01+p*a;
                q = q+a/x;
            }
            result = q;
            return result;
        }


        private static double gammastirf(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double y = 0;
            double w = 0;
            double v = 0;
            double stir = 0;

            w = 1/x;
            stir = 7.87311395793093628397E-4;
            stir = -2.29549961613378126380E-4+w*stir;
            stir = -2.68132617805781232825E-3+w*stir;
            stir = 3.47222221605458667310E-3+w*stir;
            stir = 8.33333333333482257126E-2+w*stir;
            w = 1+w*stir;
            y = Math.Exp(x);
            if( (double)(x)>(double)(143.01608) )
            {
                v = Math.Pow(x, 0.5*x-0.25);
                y = v*(v/y);
            }
            else
            {
                y = Math.Pow(x, x-0.5)/y;
            }
            result = 2.50662827463100050242*y*w;
            return result;
        }


    }
    public class normaldistr
    {
        /*************************************************************************
        Error function

        The integral is

                                  x
                                   -
                        2         | |          2
          erf(x)  =  --------     |    exp( - t  ) dt.
                     sqrt(pi)   | |
                                 -
                                  0

        For 0 <= |x| < 1, erf(x) = x * P4(x**2)/Q5(x**2); otherwise
        erf(x) = 1 - erfc(x).


        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE      0,1         30000       3.7e-16     1.0e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double errorfunction(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double xsq = 0;
            double s = 0;
            double p = 0;
            double q = 0;

            s = Math.Sign(x);
            x = Math.Abs(x);
            if( (double)(x)<(double)(0.5) )
            {
                xsq = x*x;
                p = 0.007547728033418631287834;
                p = -0.288805137207594084924010+xsq*p;
                p = 14.3383842191748205576712+xsq*p;
                p = 38.0140318123903008244444+xsq*p;
                p = 3017.82788536507577809226+xsq*p;
                p = 7404.07142710151470082064+xsq*p;
                p = 80437.3630960840172832162+xsq*p;
                q = 0.0;
                q = 1.00000000000000000000000+xsq*q;
                q = 38.0190713951939403753468+xsq*q;
                q = 658.070155459240506326937+xsq*q;
                q = 6379.60017324428279487120+xsq*q;
                q = 34216.5257924628539769006+xsq*q;
                q = 80437.3630960840172826266+xsq*q;
                result = s*1.1283791670955125738961589031*x*p/q;
                return result;
            }
            if( (double)(x)>=(double)(10) )
            {
                result = s;
                return result;
            }
            result = s*(1-errorfunctionc(x, _params));
            return result;
        }


        /*************************************************************************
        Complementary error function

         1 - erf(x) =

                                  inf.
                                    -
                         2         | |          2
          erfc(x)  =  --------     |    exp( - t  ) dt
                      sqrt(pi)   | |
                                  -
                                   x


        For small x, erfc(x) = 1 - erf(x); otherwise rational
        approximations are computed.


        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE      0,26.6417   30000       5.7e-14     1.5e-14

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double errorfunctionc(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double p = 0;
            double q = 0;

            if( (double)(x)<(double)(0) )
            {
                result = 2-errorfunctionc(-x, _params);
                return result;
            }
            if( (double)(x)<(double)(0.5) )
            {
                result = 1.0-errorfunction(x, _params);
                return result;
            }
            if( (double)(x)>=(double)(10) )
            {
                result = 0;
                return result;
            }
            p = 0.0;
            p = 0.5641877825507397413087057563+x*p;
            p = 9.675807882987265400604202961+x*p;
            p = 77.08161730368428609781633646+x*p;
            p = 368.5196154710010637133875746+x*p;
            p = 1143.262070703886173606073338+x*p;
            p = 2320.439590251635247384768711+x*p;
            p = 2898.0293292167655611275846+x*p;
            p = 1826.3348842295112592168999+x*p;
            q = 1.0;
            q = 17.14980943627607849376131193+x*q;
            q = 137.1255960500622202878443578+x*q;
            q = 661.7361207107653469211984771+x*q;
            q = 2094.384367789539593790281779+x*q;
            q = 4429.612803883682726711528526+x*q;
            q = 6089.5424232724435504633068+x*q;
            q = 4958.82756472114071495438422+x*q;
            q = 1826.3348842295112595576438+x*q;
            result = Math.Exp(-math.sqr(x))*p/q;
            return result;
        }


        /*************************************************************************
        Same as normalcdf(), obsolete name.
        *************************************************************************/
        public static double normaldistribution(double x,
            alglib.xparams _params)
        {
            double result = 0;

            result = 0.5*(errorfunction(x/1.41421356237309504880, _params)+1);
            return result;
        }


        /*************************************************************************
        Normal distribution PDF

        Returns Gaussian probability density function:

                       1
           f(x)  = --------- * exp(-x^2/2)
                   sqrt(2pi)

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double normalpdf(double x,
            alglib.xparams _params)
        {
            double result = 0;

            alglib.ap.assert(math.isfinite(x), "NormalPDF: X is infinite");
            result = Math.Exp(-(x*x/2))/Math.Sqrt(2*Math.PI);
            return result;
        }


        /*************************************************************************
        Normal distribution CDF

        Returns the area under the Gaussian probability density
        function, integrated from minus infinity to x:

                                   x
                                    -
                          1        | |          2
           ndtr(x)  = ---------    |    exp( - t /2 ) dt
                      sqrt(2pi)  | |
                                  -
                                 -inf.

                    =  ( 1 + erf(z) ) / 2
                    =  erfc(z) / 2

        where z = x/sqrt(2). Computation is via the functions
        erf and erfc.


        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE     -13,0        30000       3.4e-14     6.7e-15

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double normalcdf(double x,
            alglib.xparams _params)
        {
            double result = 0;

            result = 0.5*(errorfunction(x/1.41421356237309504880, _params)+1);
            return result;
        }


        /*************************************************************************
        Inverse of the error function

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double inverf(double e,
            alglib.xparams _params)
        {
            double result = 0;

            result = invnormaldistribution(0.5*(e+1), _params)/Math.Sqrt(2);
            return result;
        }


        /*************************************************************************
        Same as invnormalcdf(), deprecated name
        *************************************************************************/
        public static double invnormaldistribution(double y0,
            alglib.xparams _params)
        {
            double result = 0;

            result = invnormalcdf(y0, _params);
            return result;
        }


        /*************************************************************************
        Inverse of Normal CDF

        Returns the argument, x, for which the area under the
        Gaussian probability density function (integrated from
        minus infinity to x) is equal to y.


        For small arguments 0 < y < exp(-2), the program computes
        z = sqrt( -2.0 * log(y) );  then the approximation is
        x = z - log(z)/z  - (1/z) P(1/z) / Q(1/z).
        There are two rational functions P/Q, one for 0 < y < exp(-32)
        and the other for y up to exp(-2).  For larger arguments,
        w = y - 0.5, and  x/sqrt(2pi) = w + w**3 R(w**2)/S(w**2)).

        ACCURACY:

                             Relative error:
        arithmetic   domain        # trials      peak         rms
           IEEE     0.125, 1        20000       7.2e-16     1.3e-16
           IEEE     3e-308, 0.135   50000       4.6e-16     9.8e-17

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1988, 1992, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double invnormalcdf(double y0,
            alglib.xparams _params)
        {
            double result = 0;
            double expm2 = 0;
            double s2pi = 0;
            double x = 0;
            double y = 0;
            double z = 0;
            double y2 = 0;
            double x0 = 0;
            double x1 = 0;
            int code = 0;
            double p0 = 0;
            double q0 = 0;
            double p1 = 0;
            double q1 = 0;
            double p2 = 0;
            double q2 = 0;

            expm2 = 0.13533528323661269189;
            s2pi = 2.50662827463100050242;
            if( (double)(y0)<=(double)(0) )
            {
                result = -math.maxrealnumber;
                return result;
            }
            if( (double)(y0)>=(double)(1) )
            {
                result = math.maxrealnumber;
                return result;
            }
            code = 1;
            y = y0;
            if( (double)(y)>(double)(1.0-expm2) )
            {
                y = 1.0-y;
                code = 0;
            }
            if( (double)(y)>(double)(expm2) )
            {
                y = y-0.5;
                y2 = y*y;
                p0 = -59.9633501014107895267;
                p0 = 98.0010754185999661536+y2*p0;
                p0 = -56.6762857469070293439+y2*p0;
                p0 = 13.9312609387279679503+y2*p0;
                p0 = -1.23916583867381258016+y2*p0;
                q0 = 1;
                q0 = 1.95448858338141759834+y2*q0;
                q0 = 4.67627912898881538453+y2*q0;
                q0 = 86.3602421390890590575+y2*q0;
                q0 = -225.462687854119370527+y2*q0;
                q0 = 200.260212380060660359+y2*q0;
                q0 = -82.0372256168333339912+y2*q0;
                q0 = 15.9056225126211695515+y2*q0;
                q0 = -1.18331621121330003142+y2*q0;
                x = y+y*y2*p0/q0;
                x = x*s2pi;
                result = x;
                return result;
            }
            x = Math.Sqrt(-(2.0*Math.Log(y)));
            x0 = x-Math.Log(x)/x;
            z = 1.0/x;
            if( (double)(x)<(double)(8.0) )
            {
                p1 = 4.05544892305962419923;
                p1 = 31.5251094599893866154+z*p1;
                p1 = 57.1628192246421288162+z*p1;
                p1 = 44.0805073893200834700+z*p1;
                p1 = 14.6849561928858024014+z*p1;
                p1 = 2.18663306850790267539+z*p1;
                p1 = -(1.40256079171354495875*0.1)+z*p1;
                p1 = -(3.50424626827848203418*0.01)+z*p1;
                p1 = -(8.57456785154685413611*0.0001)+z*p1;
                q1 = 1;
                q1 = 15.7799883256466749731+z*q1;
                q1 = 45.3907635128879210584+z*q1;
                q1 = 41.3172038254672030440+z*q1;
                q1 = 15.0425385692907503408+z*q1;
                q1 = 2.50464946208309415979+z*q1;
                q1 = -(1.42182922854787788574*0.1)+z*q1;
                q1 = -(3.80806407691578277194*0.01)+z*q1;
                q1 = -(9.33259480895457427372*0.0001)+z*q1;
                x1 = z*p1/q1;
            }
            else
            {
                p2 = 3.23774891776946035970;
                p2 = 6.91522889068984211695+z*p2;
                p2 = 3.93881025292474443415+z*p2;
                p2 = 1.33303460815807542389+z*p2;
                p2 = 2.01485389549179081538*0.1+z*p2;
                p2 = 1.23716634817820021358*0.01+z*p2;
                p2 = 3.01581553508235416007*0.0001+z*p2;
                p2 = 2.65806974686737550832*0.000001+z*p2;
                p2 = 6.23974539184983293730*0.000000001+z*p2;
                q2 = 1;
                q2 = 6.02427039364742014255+z*q2;
                q2 = 3.67983563856160859403+z*q2;
                q2 = 1.37702099489081330271+z*q2;
                q2 = 2.16236993594496635890*0.1+z*q2;
                q2 = 1.34204006088543189037*0.01+z*q2;
                q2 = 3.28014464682127739104*0.0001+z*q2;
                q2 = 2.89247864745380683936*0.000001+z*q2;
                q2 = 6.79019408009981274425*0.000000001+z*q2;
                x1 = z*p2/q2;
            }
            x = x0-x1;
            if( code!=0 )
            {
                x = -x;
            }
            result = x;
            return result;
        }


        /*************************************************************************
        Bivariate normal PDF

        Returns probability density function of the bivariate  Gaussian  with
        correlation parameter equal to Rho:

                                 1              (    x^2 - 2*rho*x*y + y^2  )
            f(x,y,rho) = ----------------- * exp( - ----------------------- )
                         2pi*sqrt(1-rho^2)      (        2*(1-rho^2)        )


        with -1<rho<+1 and arbitrary x, y.

        This function won't fail as long as Rho is in (-1,+1) range.

          -- ALGLIB --
             Copyright 15.11.2019 by Bochkanov Sergey
        *************************************************************************/
        public static double bivariatenormalpdf(double x,
            double y,
            double rho,
            alglib.xparams _params)
        {
            double result = 0;
            double onerho2 = 0;

            alglib.ap.assert(math.isfinite(x), "BivariateNormalCDF: X is infinite");
            alglib.ap.assert(math.isfinite(y), "BivariateNormalCDF: Y is infinite");
            alglib.ap.assert(math.isfinite(rho), "BivariateNormalCDF: Rho is infinite");
            alglib.ap.assert((double)(-1)<(double)(rho) && (double)(rho)<(double)(1), "BivariateNormalCDF: Rho is not in (-1,+1) range");
            onerho2 = (1-rho)*(1+rho);
            result = Math.Exp(-((x*x+y*y-2*rho*x*y)/(2*onerho2)))/(2*Math.PI*Math.Sqrt(onerho2));
            return result;
        }


        /*************************************************************************
        Bivariate normal CDF

        Returns the area under the bivariate Gaussian  PDF  with  correlation
        parameter equal to Rho, integrated from minus infinity to (x,y):


                                                  x      y
                                                  -      -  
                                    1            | |    | | 
            bvn(x,y,rho) = -------------------   |      |   f(u,v,rho)*du*dv
                            2pi*sqrt(1-rho^2)  | |    | |    
                                                -      -
                                               -INF   -INF

                                               
        where

                              (    u^2 - 2*rho*u*v + v^2  )
            f(u,v,rho)   = exp( - ----------------------- )
                              (        2*(1-rho^2)        )


        with -1<rho<+1 and arbitrary x, y.

        This subroutine uses high-precision approximation scheme proposed  by
        Alan Genz in "Numerical  Computation  of  Rectangular  Bivariate  and
        Trivariate Normal and  t  probabilities",  which  computes  CDF  with
        absolute error roughly equal to 1e-14.

        This function won't fail as long as Rho is in (-1,+1) range.

          -- ALGLIB --
             Copyright 15.11.2019 by Bochkanov Sergey
        *************************************************************************/
        public static double bivariatenormalcdf(double x,
            double y,
            double rho,
            alglib.xparams _params)
        {
            double result = 0;
            double rangea = 0;
            double rangeb = 0;
            double s = 0;
            double v = 0;
            double v0 = 0;
            double v1 = 0;
            double fxys = 0;
            double ta = 0;
            double tb = 0;
            double tc = 0;

            alglib.ap.assert(math.isfinite(x), "BivariateNormalCDF: X is infinite");
            alglib.ap.assert(math.isfinite(y), "BivariateNormalCDF: Y is infinite");
            alglib.ap.assert(math.isfinite(rho), "BivariateNormalCDF: Rho is infinite");
            alglib.ap.assert((double)(-1)<(double)(rho) && (double)(rho)<(double)(1), "BivariateNormalCDF: Rho is not in (-1,+1) range");
            if( (double)(rho)==(double)(0) )
            {
                result = normalcdf(x, _params)*normalcdf(y, _params);
                return result;
            }
            if( (double)(Math.Abs(rho))<=(double)(0.8) )
            {
                
                //
                // Rho is small, compute integral using using formula (3) by Alan Genz, integrated
                // by means of 10-point Gauss-Legendre quadrature
                //
                rangea = 0;
                rangeb = Math.Asin(rho);
                v = 0;
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.2491470458134028, -0.1252334085114689, _params);
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.2491470458134028, 0.1252334085114689, _params);
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.2334925365383548, -0.3678314989981802, _params);
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.2334925365383548, 0.3678314989981802, _params);
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.2031674267230659, -0.5873179542866175, _params);
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.2031674267230659, 0.5873179542866175, _params);
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.1600783285433462, -0.7699026741943047, _params);
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.1600783285433462, 0.7699026741943047, _params);
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.1069393259953184, -0.9041172563704749, _params);
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.1069393259953184, 0.9041172563704749, _params);
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.0471753363865118, -0.9815606342467192, _params);
                v = v+bvnintegrate3(rangea, rangeb, x, y, 0.0471753363865118, 0.9815606342467192, _params);
                v = v*0.5*(rangeb-rangea)/(2*Math.PI);
                result = normalcdf(x, _params)*normalcdf(y, _params)+v;
            }
            else
            {
                
                //
                // Rho is large, compute integral using using formula (6) by Alan Genz, integrated
                // by means of 20-point Gauss-Legendre quadrature.
                //
                x = -x;
                y = -y;
                s = Math.Sign(rho);
                if( (double)(s)>(double)(0) )
                {
                    fxys = normalcdf(-Math.Max(x, y), _params);
                }
                else
                {
                    fxys = Math.Max(0.0, normalcdf(-x, _params)-normalcdf(y, _params));
                }
                rangea = 0;
                rangeb = Math.Sqrt((1-rho)*(1+rho));
                
                //
                // Compute first term (analytic integral) from formula (6)
                //
                ta = rangeb;
                tb = Math.Abs(x-s*y);
                tc = (4-s*x*y)/8;
                v0 = ta*(1-tc*(tb*tb-ta*ta)/3)*Math.Exp(-(tb*tb/(2*ta*ta)))-tb*(1-tc*tb*tb/3)*Math.Sqrt(2*Math.PI)*normalcdf(-(tb/ta), _params);
                v0 = v0*Math.Exp(-(s*x*y/2))/(2*Math.PI);
                
                //
                // Compute second term (numerical integral, 20-point Gauss-Legendre rule) from formula (6)
                //
                v1 = 0;
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1527533871307258, -0.0765265211334973, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1527533871307258, 0.0765265211334973, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1491729864726037, -0.2277858511416451, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1491729864726037, 0.2277858511416451, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1420961093183820, -0.3737060887154195, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1420961093183820, 0.3737060887154195, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1316886384491766, -0.5108670019508271, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1316886384491766, 0.5108670019508271, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1181945319615184, -0.6360536807265150, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1181945319615184, 0.6360536807265150, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1019301198172404, -0.7463319064601508, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.1019301198172404, 0.7463319064601508, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.0832767415767048, -0.8391169718222188, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.0832767415767048, 0.8391169718222188, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.0626720483341091, -0.9122344282513259, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.0626720483341091, 0.9122344282513259, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.0406014298003869, -0.9639719272779138, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.0406014298003869, 0.9639719272779138, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.0176140071391521, -0.9931285991850949, _params);
                v1 = v1+bvnintegrate6(rangea, rangeb, x, y, s, 0.0176140071391521, 0.9931285991850949, _params);
                v1 = v1*0.5*(rangeb-rangea)/(2*Math.PI);
                result = fxys-s*(v0+v1);
            }
            result = Math.Max(result, 0);
            result = Math.Min(result, 1);
            return result;
        }


        /*************************************************************************
        Internal function which computes integrand of  formula  (3)  by  Alan
        Genz times Gaussian weights (passed by user).

          -- ALGLIB --
             Copyright 15.11.2019 by Bochkanov Sergey
        *************************************************************************/
        private static double bvnintegrate3(double rangea,
            double rangeb,
            double x,
            double y,
            double gw,
            double gx,
            alglib.xparams _params)
        {
            double result = 0;
            double r = 0;
            double t2 = 0;
            double dd = 0;
            double sinr = 0;
            double cosr = 0;

            r = (rangeb-rangea)*0.5*gx+(rangeb+rangea)*0.5;
            t2 = Math.Tan(0.5*r);
            dd = 1/(1+t2*t2);
            sinr = 2*t2*dd;
            cosr = (1-t2*t2)*dd;
            result = gw*Math.Exp(-((x*x+y*y-2*x*y*sinr)/(2*cosr*cosr)));
            return result;
        }


        /*************************************************************************
        Internal function which computes integrand of  formula  (6)  by  Alan
        Genz times Gaussian weights (passed by user).

          -- ALGLIB --
             Copyright 15.11.2019 by Bochkanov Sergey
        *************************************************************************/
        private static double bvnintegrate6(double rangea,
            double rangeb,
            double x,
            double y,
            double s,
            double gw,
            double gx,
            alglib.xparams _params)
        {
            double result = 0;
            double r = 0;
            double exphsk22x2 = 0;
            double exphsk2 = 0;
            double sqrt1x2 = 0;
            double exphsk1sqrt1x2 = 0;

            r = (rangeb-rangea)*0.5*gx+(rangeb+rangea)*0.5;
            exphsk22x2 = Math.Exp(-((x-s*y)*(x-s*y)/(2*r*r)));
            exphsk2 = Math.Exp(-(x*s*y/2));
            sqrt1x2 = Math.Sqrt((1-r)*(1+r));
            exphsk1sqrt1x2 = Math.Exp(-(x*s*y/(1+sqrt1x2)));
            result = gw*exphsk22x2*(exphsk1sqrt1x2/sqrt1x2-exphsk2*(1+(4-x*y*s)*r*r/8));
            return result;
        }


    }
    public class ibetaf
    {
        /*************************************************************************
        Incomplete beta integral

        Returns incomplete beta integral of the arguments, evaluated
        from zero to x.  The function is defined as

                         x
            -            -
           | (a+b)      | |  a-1     b-1
         -----------    |   t   (1-t)   dt.
          -     -     | |
         | (a) | (b)   -
                        0

        The domain of definition is 0 <= x <= 1.  In this
        implementation a and b are restricted to positive values.
        The integral from x to 1 may be obtained by the symmetry
        relation

           1 - incbet( a, b, x )  =  incbet( b, a, 1-x ).

        The integral is evaluated by a continued fraction expansion
        or, when b*x is small, by a power series.

        ACCURACY:

        Tested at uniformly distributed random points (a,b,x) with a and b
        in "domain" and x between 0 and 1.
                                               Relative error
        arithmetic   domain     # trials      peak         rms
           IEEE      0,5         10000       6.9e-15     4.5e-16
           IEEE      0,85       250000       2.2e-13     1.7e-14
           IEEE      0,1000      30000       5.3e-12     6.3e-13
           IEEE      0,10000    250000       9.3e-11     7.1e-12
           IEEE      0,100000    10000       8.7e-10     4.8e-11
        Outputs smaller than the IEEE gradual underflow threshold
        were excluded from these statistics.

        Cephes Math Library, Release 2.8:  June, 2000
        Copyright 1984, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double incompletebeta(double a,
            double b,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double t = 0;
            double xc = 0;
            double w = 0;
            double y = 0;
            int flag = 0;
            double sg = 0;
            double big = 0;
            double biginv = 0;
            double maxgam = 0;
            double minlog = 0;
            double maxlog = 0;

            big = 4.503599627370496e15;
            biginv = 2.22044604925031308085e-16;
            maxgam = 171.624376956302725;
            minlog = Math.Log(math.minrealnumber);
            maxlog = Math.Log(math.maxrealnumber);
            alglib.ap.assert((double)(a)>(double)(0) && (double)(b)>(double)(0), "Domain error in IncompleteBeta");
            alglib.ap.assert((double)(x)>=(double)(0) && (double)(x)<=(double)(1), "Domain error in IncompleteBeta");
            if( (double)(x)==(double)(0) )
            {
                result = 0;
                return result;
            }
            if( (double)(x)==(double)(1) )
            {
                result = 1;
                return result;
            }
            flag = 0;
            if( (double)(b*x)<=(double)(1.0) && (double)(x)<=(double)(0.95) )
            {
                result = incompletebetaps(a, b, x, maxgam, _params);
                return result;
            }
            w = 1.0-x;
            if( (double)(x)>(double)(a/(a+b)) )
            {
                flag = 1;
                t = a;
                a = b;
                b = t;
                xc = x;
                x = w;
            }
            else
            {
                xc = w;
            }
            if( (flag==1 && (double)(b*x)<=(double)(1.0)) && (double)(x)<=(double)(0.95) )
            {
                t = incompletebetaps(a, b, x, maxgam, _params);
                if( (double)(t)<=(double)(math.machineepsilon) )
                {
                    result = 1.0-math.machineepsilon;
                }
                else
                {
                    result = 1.0-t;
                }
                return result;
            }
            y = x*(a+b-2.0)-(a-1.0);
            if( (double)(y)<(double)(0.0) )
            {
                w = incompletebetafe(a, b, x, big, biginv, _params);
            }
            else
            {
                w = incompletebetafe2(a, b, x, big, biginv, _params)/xc;
            }
            y = a*Math.Log(x);
            t = b*Math.Log(xc);
            if( ((double)(a+b)<(double)(maxgam) && (double)(Math.Abs(y))<(double)(maxlog)) && (double)(Math.Abs(t))<(double)(maxlog) )
            {
                t = Math.Pow(xc, b);
                t = t*Math.Pow(x, a);
                t = t/a;
                t = t*w;
                t = t*(gammafunc.gammafunction(a+b, _params)/(gammafunc.gammafunction(a, _params)*gammafunc.gammafunction(b, _params)));
                if( flag==1 )
                {
                    if( (double)(t)<=(double)(math.machineepsilon) )
                    {
                        result = 1.0-math.machineepsilon;
                    }
                    else
                    {
                        result = 1.0-t;
                    }
                }
                else
                {
                    result = t;
                }
                return result;
            }
            y = y+t+gammafunc.lngamma(a+b, ref sg, _params)-gammafunc.lngamma(a, ref sg, _params)-gammafunc.lngamma(b, ref sg, _params);
            y = y+Math.Log(w/a);
            if( (double)(y)<(double)(minlog) )
            {
                t = 0.0;
            }
            else
            {
                t = Math.Exp(y);
            }
            if( flag==1 )
            {
                if( (double)(t)<=(double)(math.machineepsilon) )
                {
                    t = 1.0-math.machineepsilon;
                }
                else
                {
                    t = 1.0-t;
                }
            }
            result = t;
            return result;
        }


        /*************************************************************************
        Inverse of imcomplete beta integral

        Given y, the function finds x such that

         incbet( a, b, x ) = y .

        The routine performs interval halving or Newton iterations to find the
        root of incbet(a,b,x) - y = 0.


        ACCURACY:

                             Relative error:
                       x     a,b
        arithmetic   domain  domain  # trials    peak       rms
           IEEE      0,1    .5,10000   50000    5.8e-12   1.3e-13
           IEEE      0,1   .25,100    100000    1.8e-13   3.9e-15
           IEEE      0,1     0,5       50000    1.1e-12   5.5e-15
        With a and b constrained to half-integer or integer values:
           IEEE      0,1    .5,10000   50000    5.8e-12   1.1e-13
           IEEE      0,1    .5,100    100000    1.7e-14   7.9e-16
        With a = .5, b constrained to half-integer or integer values:
           IEEE      0,1    .5,10000   10000    8.3e-11   1.0e-11

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1996, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double invincompletebeta(double a,
            double b,
            double y,
            alglib.xparams _params)
        {
            double result = 0;
            double aaa = 0;
            double bbb = 0;
            double y0 = 0;
            double d = 0;
            double yyy = 0;
            double x = 0;
            double x0 = 0;
            double x1 = 0;
            double lgm = 0;
            double yp = 0;
            double di = 0;
            double dithresh = 0;
            double yl = 0;
            double yh = 0;
            double xt = 0;
            int i = 0;
            int rflg = 0;
            int dir = 0;
            int nflg = 0;
            double s = 0;
            int mainlooppos = 0;
            int ihalve = 0;
            int ihalvecycle = 0;
            int newt = 0;
            int newtcycle = 0;
            int breaknewtcycle = 0;
            int breakihalvecycle = 0;

            i = 0;
            alglib.ap.assert((double)(y)>=(double)(0) && (double)(y)<=(double)(1), "Domain error in InvIncompleteBeta");
            
            //
            // special cases
            //
            if( (double)(y)==(double)(0) )
            {
                result = 0;
                return result;
            }
            if( (double)(y)==(double)(1.0) )
            {
                result = 1;
                return result;
            }
            
            //
            // these initializations are not really necessary,
            // but without them compiler complains about 'possibly uninitialized variables'.
            //
            dithresh = 0;
            rflg = 0;
            aaa = 0;
            bbb = 0;
            y0 = 0;
            x = 0;
            yyy = 0;
            lgm = 0;
            dir = 0;
            di = 0;
            
            //
            // normal initializations
            //
            x0 = 0.0;
            yl = 0.0;
            x1 = 1.0;
            yh = 1.0;
            nflg = 0;
            mainlooppos = 0;
            ihalve = 1;
            ihalvecycle = 2;
            newt = 3;
            newtcycle = 4;
            breaknewtcycle = 5;
            breakihalvecycle = 6;
            
            //
            // main loop
            //
            while( true )
            {
                
                //
                // start
                //
                if( mainlooppos==0 )
                {
                    if( (double)(a)<=(double)(1.0) || (double)(b)<=(double)(1.0) )
                    {
                        dithresh = 1.0e-6;
                        rflg = 0;
                        aaa = a;
                        bbb = b;
                        y0 = y;
                        x = aaa/(aaa+bbb);
                        yyy = incompletebeta(aaa, bbb, x, _params);
                        mainlooppos = ihalve;
                        continue;
                    }
                    else
                    {
                        dithresh = 1.0e-4;
                    }
                    yp = -normaldistr.invnormaldistribution(y, _params);
                    if( (double)(y)>(double)(0.5) )
                    {
                        rflg = 1;
                        aaa = b;
                        bbb = a;
                        y0 = 1.0-y;
                        yp = -yp;
                    }
                    else
                    {
                        rflg = 0;
                        aaa = a;
                        bbb = b;
                        y0 = y;
                    }
                    lgm = (yp*yp-3.0)/6.0;
                    x = 2.0/(1.0/(2.0*aaa-1.0)+1.0/(2.0*bbb-1.0));
                    d = yp*Math.Sqrt(x+lgm)/x-(1.0/(2.0*bbb-1.0)-1.0/(2.0*aaa-1.0))*(lgm+5.0/6.0-2.0/(3.0*x));
                    d = 2.0*d;
                    if( (double)(d)<(double)(Math.Log(math.minrealnumber)) )
                    {
                        x = 0;
                        break;
                    }
                    x = aaa/(aaa+bbb*Math.Exp(d));
                    yyy = incompletebeta(aaa, bbb, x, _params);
                    yp = (yyy-y0)/y0;
                    if( (double)(Math.Abs(yp))<(double)(0.2) )
                    {
                        mainlooppos = newt;
                        continue;
                    }
                    mainlooppos = ihalve;
                    continue;
                }
                
                //
                // ihalve
                //
                if( mainlooppos==ihalve )
                {
                    dir = 0;
                    di = 0.5;
                    i = 0;
                    mainlooppos = ihalvecycle;
                    continue;
                }
                
                //
                // ihalvecycle
                //
                if( mainlooppos==ihalvecycle )
                {
                    if( i<=99 )
                    {
                        if( i!=0 )
                        {
                            x = x0+di*(x1-x0);
                            if( (double)(x)==(double)(1.0) )
                            {
                                x = 1.0-math.machineepsilon;
                            }
                            if( (double)(x)==(double)(0.0) )
                            {
                                di = 0.5;
                                x = x0+di*(x1-x0);
                                if( (double)(x)==(double)(0.0) )
                                {
                                    break;
                                }
                            }
                            yyy = incompletebeta(aaa, bbb, x, _params);
                            yp = (x1-x0)/(x1+x0);
                            if( (double)(Math.Abs(yp))<(double)(dithresh) )
                            {
                                mainlooppos = newt;
                                continue;
                            }
                            yp = (yyy-y0)/y0;
                            if( (double)(Math.Abs(yp))<(double)(dithresh) )
                            {
                                mainlooppos = newt;
                                continue;
                            }
                        }
                        if( (double)(yyy)<(double)(y0) )
                        {
                            x0 = x;
                            yl = yyy;
                            if( dir<0 )
                            {
                                dir = 0;
                                di = 0.5;
                            }
                            else
                            {
                                if( dir>3 )
                                {
                                    di = 1.0-(1.0-di)*(1.0-di);
                                }
                                else
                                {
                                    if( dir>1 )
                                    {
                                        di = 0.5*di+0.5;
                                    }
                                    else
                                    {
                                        di = (y0-yyy)/(yh-yl);
                                    }
                                }
                            }
                            dir = dir+1;
                            if( (double)(x0)>(double)(0.75) )
                            {
                                if( rflg==1 )
                                {
                                    rflg = 0;
                                    aaa = a;
                                    bbb = b;
                                    y0 = y;
                                }
                                else
                                {
                                    rflg = 1;
                                    aaa = b;
                                    bbb = a;
                                    y0 = 1.0-y;
                                }
                                x = 1.0-x;
                                yyy = incompletebeta(aaa, bbb, x, _params);
                                x0 = 0.0;
                                yl = 0.0;
                                x1 = 1.0;
                                yh = 1.0;
                                mainlooppos = ihalve;
                                continue;
                            }
                        }
                        else
                        {
                            x1 = x;
                            if( rflg==1 && (double)(x1)<(double)(math.machineepsilon) )
                            {
                                x = 0.0;
                                break;
                            }
                            yh = yyy;
                            if( dir>0 )
                            {
                                dir = 0;
                                di = 0.5;
                            }
                            else
                            {
                                if( dir<-3 )
                                {
                                    di = di*di;
                                }
                                else
                                {
                                    if( dir<-1 )
                                    {
                                        di = 0.5*di;
                                    }
                                    else
                                    {
                                        di = (yyy-y0)/(yh-yl);
                                    }
                                }
                            }
                            dir = dir-1;
                        }
                        i = i+1;
                        mainlooppos = ihalvecycle;
                        continue;
                    }
                    else
                    {
                        mainlooppos = breakihalvecycle;
                        continue;
                    }
                }
                
                //
                // breakihalvecycle
                //
                if( mainlooppos==breakihalvecycle )
                {
                    if( (double)(x0)>=(double)(1.0) )
                    {
                        x = 1.0-math.machineepsilon;
                        break;
                    }
                    if( (double)(x)<=(double)(0.0) )
                    {
                        x = 0.0;
                        break;
                    }
                    mainlooppos = newt;
                    continue;
                }
                
                //
                // newt
                //
                if( mainlooppos==newt )
                {
                    if( nflg!=0 )
                    {
                        break;
                    }
                    nflg = 1;
                    lgm = gammafunc.lngamma(aaa+bbb, ref s, _params)-gammafunc.lngamma(aaa, ref s, _params)-gammafunc.lngamma(bbb, ref s, _params);
                    i = 0;
                    mainlooppos = newtcycle;
                    continue;
                }
                
                //
                // newtcycle
                //
                if( mainlooppos==newtcycle )
                {
                    if( i<=7 )
                    {
                        if( i!=0 )
                        {
                            yyy = incompletebeta(aaa, bbb, x, _params);
                        }
                        if( (double)(yyy)<(double)(yl) )
                        {
                            x = x0;
                            yyy = yl;
                        }
                        else
                        {
                            if( (double)(yyy)>(double)(yh) )
                            {
                                x = x1;
                                yyy = yh;
                            }
                            else
                            {
                                if( (double)(yyy)<(double)(y0) )
                                {
                                    x0 = x;
                                    yl = yyy;
                                }
                                else
                                {
                                    x1 = x;
                                    yh = yyy;
                                }
                            }
                        }
                        if( (double)(x)==(double)(1.0) || (double)(x)==(double)(0.0) )
                        {
                            mainlooppos = breaknewtcycle;
                            continue;
                        }
                        d = (aaa-1.0)*Math.Log(x)+(bbb-1.0)*Math.Log(1.0-x)+lgm;
                        if( (double)(d)<(double)(Math.Log(math.minrealnumber)) )
                        {
                            break;
                        }
                        if( (double)(d)>(double)(Math.Log(math.maxrealnumber)) )
                        {
                            mainlooppos = breaknewtcycle;
                            continue;
                        }
                        d = Math.Exp(d);
                        d = (yyy-y0)/d;
                        xt = x-d;
                        if( (double)(xt)<=(double)(x0) )
                        {
                            yyy = (x-x0)/(x1-x0);
                            xt = x0+0.5*yyy*(x-x0);
                            if( (double)(xt)<=(double)(0.0) )
                            {
                                mainlooppos = breaknewtcycle;
                                continue;
                            }
                        }
                        if( (double)(xt)>=(double)(x1) )
                        {
                            yyy = (x1-x)/(x1-x0);
                            xt = x1-0.5*yyy*(x1-x);
                            if( (double)(xt)>=(double)(1.0) )
                            {
                                mainlooppos = breaknewtcycle;
                                continue;
                            }
                        }
                        x = xt;
                        if( (double)(Math.Abs(d/x))<(double)(128.0*math.machineepsilon) )
                        {
                            break;
                        }
                        i = i+1;
                        mainlooppos = newtcycle;
                        continue;
                    }
                    else
                    {
                        mainlooppos = breaknewtcycle;
                        continue;
                    }
                }
                
                //
                // breaknewtcycle
                //
                if( mainlooppos==breaknewtcycle )
                {
                    dithresh = 256.0*math.machineepsilon;
                    mainlooppos = ihalve;
                    continue;
                }
            }
            
            //
            // done
            //
            if( rflg!=0 )
            {
                if( (double)(x)<=(double)(math.machineepsilon) )
                {
                    x = 1.0-math.machineepsilon;
                }
                else
                {
                    x = 1.0-x;
                }
            }
            result = x;
            return result;
        }


        /*************************************************************************
        Continued fraction expansion #1 for incomplete beta integral

        Cephes Math Library, Release 2.8:  June, 2000
        Copyright 1984, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        private static double incompletebetafe(double a,
            double b,
            double x,
            double big,
            double biginv,
            alglib.xparams _params)
        {
            double result = 0;
            double xk = 0;
            double pk = 0;
            double pkm1 = 0;
            double pkm2 = 0;
            double qk = 0;
            double qkm1 = 0;
            double qkm2 = 0;
            double k1 = 0;
            double k2 = 0;
            double k3 = 0;
            double k4 = 0;
            double k5 = 0;
            double k6 = 0;
            double k7 = 0;
            double k8 = 0;
            double r = 0;
            double t = 0;
            double ans = 0;
            double thresh = 0;
            int n = 0;

            k1 = a;
            k2 = a+b;
            k3 = a;
            k4 = a+1.0;
            k5 = 1.0;
            k6 = b-1.0;
            k7 = k4;
            k8 = a+2.0;
            pkm2 = 0.0;
            qkm2 = 1.0;
            pkm1 = 1.0;
            qkm1 = 1.0;
            ans = 1.0;
            r = 1.0;
            n = 0;
            thresh = 3.0*math.machineepsilon;
            do
            {
                xk = -(x*k1*k2/(k3*k4));
                pk = pkm1+pkm2*xk;
                qk = qkm1+qkm2*xk;
                pkm2 = pkm1;
                pkm1 = pk;
                qkm2 = qkm1;
                qkm1 = qk;
                xk = x*k5*k6/(k7*k8);
                pk = pkm1+pkm2*xk;
                qk = qkm1+qkm2*xk;
                pkm2 = pkm1;
                pkm1 = pk;
                qkm2 = qkm1;
                qkm1 = qk;
                if( (double)(qk)!=(double)(0) )
                {
                    r = pk/qk;
                }
                if( (double)(r)!=(double)(0) )
                {
                    t = Math.Abs((ans-r)/r);
                    ans = r;
                }
                else
                {
                    t = 1.0;
                }
                if( (double)(t)<(double)(thresh) )
                {
                    break;
                }
                k1 = k1+1.0;
                k2 = k2+1.0;
                k3 = k3+2.0;
                k4 = k4+2.0;
                k5 = k5+1.0;
                k6 = k6-1.0;
                k7 = k7+2.0;
                k8 = k8+2.0;
                if( (double)(Math.Abs(qk)+Math.Abs(pk))>(double)(big) )
                {
                    pkm2 = pkm2*biginv;
                    pkm1 = pkm1*biginv;
                    qkm2 = qkm2*biginv;
                    qkm1 = qkm1*biginv;
                }
                if( (double)(Math.Abs(qk))<(double)(biginv) || (double)(Math.Abs(pk))<(double)(biginv) )
                {
                    pkm2 = pkm2*big;
                    pkm1 = pkm1*big;
                    qkm2 = qkm2*big;
                    qkm1 = qkm1*big;
                }
                n = n+1;
            }
            while( n!=300 );
            result = ans;
            return result;
        }


        /*************************************************************************
        Continued fraction expansion #2
        for incomplete beta integral

        Cephes Math Library, Release 2.8:  June, 2000
        Copyright 1984, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        private static double incompletebetafe2(double a,
            double b,
            double x,
            double big,
            double biginv,
            alglib.xparams _params)
        {
            double result = 0;
            double xk = 0;
            double pk = 0;
            double pkm1 = 0;
            double pkm2 = 0;
            double qk = 0;
            double qkm1 = 0;
            double qkm2 = 0;
            double k1 = 0;
            double k2 = 0;
            double k3 = 0;
            double k4 = 0;
            double k5 = 0;
            double k6 = 0;
            double k7 = 0;
            double k8 = 0;
            double r = 0;
            double t = 0;
            double ans = 0;
            double z = 0;
            double thresh = 0;
            int n = 0;

            k1 = a;
            k2 = b-1.0;
            k3 = a;
            k4 = a+1.0;
            k5 = 1.0;
            k6 = a+b;
            k7 = a+1.0;
            k8 = a+2.0;
            pkm2 = 0.0;
            qkm2 = 1.0;
            pkm1 = 1.0;
            qkm1 = 1.0;
            z = x/(1.0-x);
            ans = 1.0;
            r = 1.0;
            n = 0;
            thresh = 3.0*math.machineepsilon;
            do
            {
                xk = -(z*k1*k2/(k3*k4));
                pk = pkm1+pkm2*xk;
                qk = qkm1+qkm2*xk;
                pkm2 = pkm1;
                pkm1 = pk;
                qkm2 = qkm1;
                qkm1 = qk;
                xk = z*k5*k6/(k7*k8);
                pk = pkm1+pkm2*xk;
                qk = qkm1+qkm2*xk;
                pkm2 = pkm1;
                pkm1 = pk;
                qkm2 = qkm1;
                qkm1 = qk;
                if( (double)(qk)!=(double)(0) )
                {
                    r = pk/qk;
                }
                if( (double)(r)!=(double)(0) )
                {
                    t = Math.Abs((ans-r)/r);
                    ans = r;
                }
                else
                {
                    t = 1.0;
                }
                if( (double)(t)<(double)(thresh) )
                {
                    break;
                }
                k1 = k1+1.0;
                k2 = k2-1.0;
                k3 = k3+2.0;
                k4 = k4+2.0;
                k5 = k5+1.0;
                k6 = k6+1.0;
                k7 = k7+2.0;
                k8 = k8+2.0;
                if( (double)(Math.Abs(qk)+Math.Abs(pk))>(double)(big) )
                {
                    pkm2 = pkm2*biginv;
                    pkm1 = pkm1*biginv;
                    qkm2 = qkm2*biginv;
                    qkm1 = qkm1*biginv;
                }
                if( (double)(Math.Abs(qk))<(double)(biginv) || (double)(Math.Abs(pk))<(double)(biginv) )
                {
                    pkm2 = pkm2*big;
                    pkm1 = pkm1*big;
                    qkm2 = qkm2*big;
                    qkm1 = qkm1*big;
                }
                n = n+1;
            }
            while( n!=300 );
            result = ans;
            return result;
        }


        /*************************************************************************
        Power series for incomplete beta integral.
        Use when b*x is small and x not too close to 1.

        Cephes Math Library, Release 2.8:  June, 2000
        Copyright 1984, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        private static double incompletebetaps(double a,
            double b,
            double x,
            double maxgam,
            alglib.xparams _params)
        {
            double result = 0;
            double s = 0;
            double t = 0;
            double u = 0;
            double v = 0;
            double n = 0;
            double t1 = 0;
            double z = 0;
            double ai = 0;
            double sg = 0;

            ai = 1.0/a;
            u = (1.0-b)*x;
            v = u/(a+1.0);
            t1 = v;
            t = u;
            n = 2.0;
            s = 0.0;
            z = math.machineepsilon*ai;
            while( (double)(Math.Abs(v))>(double)(z) )
            {
                u = (n-b)*x/n;
                t = t*u;
                v = t/(a+n);
                s = s+v;
                n = n+1.0;
            }
            s = s+t1;
            s = s+ai;
            u = a*Math.Log(x);
            if( (double)(a+b)<(double)(maxgam) && (double)(Math.Abs(u))<(double)(Math.Log(math.maxrealnumber)) )
            {
                t = gammafunc.gammafunction(a+b, _params)/(gammafunc.gammafunction(a, _params)*gammafunc.gammafunction(b, _params));
                s = s*t*Math.Pow(x, a);
            }
            else
            {
                t = gammafunc.lngamma(a+b, ref sg, _params)-gammafunc.lngamma(a, ref sg, _params)-gammafunc.lngamma(b, ref sg, _params)+u+Math.Log(s);
                if( (double)(t)<(double)(Math.Log(math.minrealnumber)) )
                {
                    s = 0.0;
                }
                else
                {
                    s = Math.Exp(t);
                }
            }
            result = s;
            return result;
        }


    }
    public class studenttdistr
    {
        /*************************************************************************
        Student's t distribution

        Computes the integral from minus infinity to t of the Student
        t distribution with integer k > 0 degrees of freedom:

                                             t
                                             -
                                            | |
                     -                      |         2   -(k+1)/2
                    | ( (k+1)/2 )           |  (     x   )
              ----------------------        |  ( 1 + --- )        dx
                            -               |  (      k  )
              sqrt( k pi ) | ( k/2 )        |
                                          | |
                                           -
                                          -inf.

        Relation to incomplete beta integral:

               1 - stdtr(k,t) = 0.5 * incbet( k/2, 1/2, z )
        where
               z = k/(k + t**2).

        For t < -2, this is the method of computation.  For higher t,
        a direct method is derived from integration by parts.
        Since the function is symmetric about t=0, the area under the
        right tail of the density is found by calling the function
        with -t instead of t.

        ACCURACY:

        Tested at random 1 <= k <= 25.  The "domain" refers to t.
                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE     -100,-2      50000       5.9e-15     1.4e-15
           IEEE     -2,100      500000       2.7e-15     4.9e-17

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double studenttdistribution(int k,
            double t,
            alglib.xparams _params)
        {
            double result = 0;
            double x = 0;
            double rk = 0;
            double z = 0;
            double f = 0;
            double tz = 0;
            double p = 0;
            double xsqk = 0;
            int j = 0;

            alglib.ap.assert(k>0, "Domain error in StudentTDistribution");
            if( (double)(t)==(double)(0) )
            {
                result = 0.5;
                return result;
            }
            if( (double)(t)<(double)(-2.0) )
            {
                rk = k;
                z = rk/(rk+t*t);
                result = 0.5*ibetaf.incompletebeta(0.5*rk, 0.5, z, _params);
                return result;
            }
            if( (double)(t)<(double)(0) )
            {
                x = -t;
            }
            else
            {
                x = t;
            }
            rk = k;
            z = 1.0+x*x/rk;
            if( k%2!=0 )
            {
                xsqk = x/Math.Sqrt(rk);
                p = Math.Atan(xsqk);
                if( k>1 )
                {
                    f = 1.0;
                    tz = 1.0;
                    j = 3;
                    while( j<=k-2 && (double)(tz/f)>(double)(math.machineepsilon) )
                    {
                        tz = tz*((j-1)/(z*j));
                        f = f+tz;
                        j = j+2;
                    }
                    p = p+f*xsqk/z;
                }
                p = p*2.0/Math.PI;
            }
            else
            {
                f = 1.0;
                tz = 1.0;
                j = 2;
                while( j<=k-2 && (double)(tz/f)>(double)(math.machineepsilon) )
                {
                    tz = tz*((j-1)/(z*j));
                    f = f+tz;
                    j = j+2;
                }
                p = f*x/Math.Sqrt(z*rk);
            }
            if( (double)(t)<(double)(0) )
            {
                p = -p;
            }
            result = 0.5+0.5*p;
            return result;
        }


        /*************************************************************************
        Functional inverse of Student's t distribution

        Given probability p, finds the argument t such that stdtr(k,t)
        is equal to p.

        ACCURACY:

        Tested at random 1 <= k <= 100.  The "domain" refers to p:
                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE    .001,.999     25000       5.7e-15     8.0e-16
           IEEE    10^-6,.001    25000       2.0e-12     2.9e-14

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double invstudenttdistribution(int k,
            double p,
            alglib.xparams _params)
        {
            double result = 0;
            double t = 0;
            double rk = 0;
            double z = 0;
            int rflg = 0;

            alglib.ap.assert((k>0 && (double)(p)>(double)(0)) && (double)(p)<(double)(1), "Domain error in InvStudentTDistribution");
            rk = k;
            if( (double)(p)>(double)(0.25) && (double)(p)<(double)(0.75) )
            {
                if( (double)(p)==(double)(0.5) )
                {
                    result = 0;
                    return result;
                }
                z = 1.0-2.0*p;
                z = ibetaf.invincompletebeta(0.5, 0.5*rk, Math.Abs(z), _params);
                t = Math.Sqrt(rk*z/(1.0-z));
                if( (double)(p)<(double)(0.5) )
                {
                    t = -t;
                }
                result = t;
                return result;
            }
            rflg = -1;
            if( (double)(p)>=(double)(0.5) )
            {
                p = 1.0-p;
                rflg = 1;
            }
            z = ibetaf.invincompletebeta(0.5*rk, 0.5, 2.0*p, _params);
            if( (double)(math.maxrealnumber*z)<(double)(rk) )
            {
                result = rflg*math.maxrealnumber;
                return result;
            }
            t = Math.Sqrt(rk/z-rk);
            result = rflg*t;
            return result;
        }


    }
    public class fdistr
    {
        /*************************************************************************
        F distribution

        Returns the area from zero to x under the F density
        function (also known as Snedcor's density or the
        variance ratio density).  This is the density
        of x = (u1/df1)/(u2/df2), where u1 and u2 are random
        variables having Chi square distributions with df1
        and df2 degrees of freedom, respectively.
        The incomplete beta integral is used, according to the
        formula

        P(x) = incbet( df1/2, df2/2, (df1*x/(df2 + df1*x) ).


        The arguments a and b are greater than zero, and x is
        nonnegative.

        ACCURACY:

        Tested at random points (a,b,x).

                       x     a,b                     Relative error:
        arithmetic  domain  domain     # trials      peak         rms
           IEEE      0,1    0,100       100000      9.8e-15     1.7e-15
           IEEE      1,5    0,100       100000      6.5e-15     3.5e-16
           IEEE      0,1    1,10000     100000      2.2e-11     3.3e-12
           IEEE      1,5    1,10000     100000      1.1e-11     1.7e-13

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double fdistribution(int a,
            int b,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double w = 0;

            alglib.ap.assert((a>=1 && b>=1) && (double)(x)>=(double)(0), "Domain error in FDistribution");
            w = a*x;
            w = w/(b+w);
            result = ibetaf.incompletebeta(0.5*a, 0.5*b, w, _params);
            return result;
        }


        /*************************************************************************
        Complemented F distribution

        Returns the area from x to infinity under the F density
        function (also known as Snedcor's density or the
        variance ratio density).


                             inf.
                              -
                     1       | |  a-1      b-1
        1-P(x)  =  ------    |   t    (1-t)    dt
                   B(a,b)  | |
                            -
                             x


        The incomplete beta integral is used, according to the
        formula

        P(x) = incbet( df2/2, df1/2, (df2/(df2 + df1*x) ).


        ACCURACY:

        Tested at random points (a,b,x) in the indicated intervals.
                       x     a,b                     Relative error:
        arithmetic  domain  domain     # trials      peak         rms
           IEEE      0,1    1,100       100000      3.7e-14     5.9e-16
           IEEE      1,5    1,100       100000      8.0e-15     1.6e-15
           IEEE      0,1    1,10000     100000      1.8e-11     3.5e-13
           IEEE      1,5    1,10000     100000      2.0e-11     3.0e-12

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double fcdistribution(int a,
            int b,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double w = 0;

            alglib.ap.assert((a>=1 && b>=1) && (double)(x)>=(double)(0), "Domain error in FCDistribution");
            w = b/(b+a*x);
            result = ibetaf.incompletebeta(0.5*b, 0.5*a, w, _params);
            return result;
        }


        /*************************************************************************
        Inverse of complemented F distribution

        Finds the F density argument x such that the integral
        from x to infinity of the F density is equal to the
        given probability p.

        This is accomplished using the inverse beta integral
        function and the relations

             z = incbi( df2/2, df1/2, p )
             x = df2 (1-z) / (df1 z).

        Note: the following relations hold for the inverse of
        the uncomplemented F distribution:

             z = incbi( df1/2, df2/2, p )
             x = df2 z / (df1 (1-z)).

        ACCURACY:

        Tested at random points (a,b,p).

                     a,b                     Relative error:
        arithmetic  domain     # trials      peak         rms
         For p between .001 and 1:
           IEEE     1,100       100000      8.3e-15     4.7e-16
           IEEE     1,10000     100000      2.1e-11     1.4e-13
         For p between 10^-6 and 10^-3:
           IEEE     1,100        50000      1.3e-12     8.4e-15
           IEEE     1,10000      50000      3.0e-12     4.8e-14

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double invfdistribution(int a,
            int b,
            double y,
            alglib.xparams _params)
        {
            double result = 0;
            double w = 0;

            alglib.ap.assert(((a>=1 && b>=1) && (double)(y)>(double)(0)) && (double)(y)<=(double)(1), "Domain error in InvFDistribution");
            
            //
            // Compute probability for x = 0.5
            //
            w = ibetaf.incompletebeta(0.5*b, 0.5*a, 0.5, _params);
            
            //
            // If that is greater than y, then the solution w < .5
            // Otherwise, solve at 1-y to remove cancellation in (b - b*w)
            //
            if( (double)(w)>(double)(y) || (double)(y)<(double)(0.001) )
            {
                w = ibetaf.invincompletebeta(0.5*b, 0.5*a, y, _params);
                result = (b-b*w)/(a*w);
            }
            else
            {
                w = ibetaf.invincompletebeta(0.5*a, 0.5*b, 1.0-y, _params);
                result = b*w/(a*(1.0-w));
            }
            return result;
        }


    }
    public class igammaf
    {
        /*************************************************************************
        Incomplete gamma integral

        The function is defined by

                                  x
                                   -
                          1       | |  -t  a-1
         igam(a,x)  =   -----     |   e   t   dt.
                         -      | |
                        | (a)    -
                                  0


        In this implementation both arguments must be positive.
        The integral is evaluated by either a power series or
        continued fraction expansion, depending on the relative
        values of a and x.

        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE      0,30       200000       3.6e-14     2.9e-15
           IEEE      0,100      300000       9.9e-14     1.5e-14

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1985, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double incompletegamma(double a,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double igammaepsilon = 0;
            double ans = 0;
            double ax = 0;
            double c = 0;
            double r = 0;
            double tmp = 0;

            igammaepsilon = 0.000000000000001;
            if( (double)(x)<=(double)(0) || (double)(a)<=(double)(0) )
            {
                result = 0;
                return result;
            }
            if( (double)(x)>(double)(1) && (double)(x)>(double)(a) )
            {
                result = 1-incompletegammac(a, x, _params);
                return result;
            }
            ax = a*Math.Log(x)-x-gammafunc.lngamma(a, ref tmp, _params);
            if( (double)(ax)<(double)(-709.78271289338399) )
            {
                result = 0;
                return result;
            }
            ax = Math.Exp(ax);
            r = a;
            c = 1;
            ans = 1;
            do
            {
                r = r+1;
                c = c*x/r;
                ans = ans+c;
            }
            while( (double)(c/ans)>(double)(igammaepsilon) );
            result = ans*ax/a;
            return result;
        }


        /*************************************************************************
        Complemented incomplete gamma integral

        The function is defined by


         igamc(a,x)   =   1 - igam(a,x)

                                   inf.
                                     -
                            1       | |  -t  a-1
                      =   -----     |   e   t   dt.
                           -      | |
                          | (a)    -
                                    x


        In this implementation both arguments must be positive.
        The integral is evaluated by either a power series or
        continued fraction expansion, depending on the relative
        values of a and x.

        ACCURACY:

        Tested at random a, x.
                       a         x                      Relative error:
        arithmetic   domain   domain     # trials      peak         rms
           IEEE     0.5,100   0,100      200000       1.9e-14     1.7e-15
           IEEE     0.01,0.5  0,100      200000       1.4e-13     1.6e-15

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1985, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double incompletegammac(double a,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double igammaepsilon = 0;
            double igammabignumber = 0;
            double igammabignumberinv = 0;
            double ans = 0;
            double ax = 0;
            double c = 0;
            double yc = 0;
            double r = 0;
            double t = 0;
            double y = 0;
            double z = 0;
            double pk = 0;
            double pkm1 = 0;
            double pkm2 = 0;
            double qk = 0;
            double qkm1 = 0;
            double qkm2 = 0;
            double tmp = 0;

            igammaepsilon = 0.000000000000001;
            igammabignumber = 4503599627370496.0;
            igammabignumberinv = 2.22044604925031308085*0.0000000000000001;
            if( (double)(x)<=(double)(0) || (double)(a)<=(double)(0) )
            {
                result = 1;
                return result;
            }
            if( (double)(x)<(double)(1) || (double)(x)<(double)(a) )
            {
                result = 1-incompletegamma(a, x, _params);
                return result;
            }
            ax = a*Math.Log(x)-x-gammafunc.lngamma(a, ref tmp, _params);
            if( (double)(ax)<(double)(-709.78271289338399) )
            {
                result = 0;
                return result;
            }
            ax = Math.Exp(ax);
            y = 1-a;
            z = x+y+1;
            c = 0;
            pkm2 = 1;
            qkm2 = x;
            pkm1 = x+1;
            qkm1 = z*x;
            ans = pkm1/qkm1;
            do
            {
                c = c+1;
                y = y+1;
                z = z+2;
                yc = y*c;
                pk = pkm1*z-pkm2*yc;
                qk = qkm1*z-qkm2*yc;
                if( (double)(qk)!=(double)(0) )
                {
                    r = pk/qk;
                    t = Math.Abs((ans-r)/r);
                    ans = r;
                }
                else
                {
                    t = 1;
                }
                pkm2 = pkm1;
                pkm1 = pk;
                qkm2 = qkm1;
                qkm1 = qk;
                if( (double)(Math.Abs(pk))>(double)(igammabignumber) )
                {
                    pkm2 = pkm2*igammabignumberinv;
                    pkm1 = pkm1*igammabignumberinv;
                    qkm2 = qkm2*igammabignumberinv;
                    qkm1 = qkm1*igammabignumberinv;
                }
            }
            while( (double)(t)>(double)(igammaepsilon) );
            result = ans*ax;
            return result;
        }


        /*************************************************************************
        Inverse of complemented imcomplete gamma integral

        Given p, the function finds x such that

         igamc( a, x ) = p.

        Starting with the approximate value

                3
         x = a t

         where

         t = 1 - d - ndtri(p) sqrt(d)

        and

         d = 1/9a,

        the routine performs up to 10 Newton iterations to find the
        root of igamc(a,x) - p = 0.

        ACCURACY:

        Tested at random a, p in the intervals indicated.

                       a        p                      Relative error:
        arithmetic   domain   domain     # trials      peak         rms
           IEEE     0.5,100   0,0.5       100000       1.0e-14     1.7e-15
           IEEE     0.01,0.5  0,0.5       100000       9.0e-14     3.4e-15
           IEEE    0.5,10000  0,0.5        20000       2.3e-13     3.8e-14

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double invincompletegammac(double a,
            double y0,
            alglib.xparams _params)
        {
            double result = 0;
            double igammaepsilon = 0;
            double iinvgammabignumber = 0;
            double x0 = 0;
            double x1 = 0;
            double x = 0;
            double yl = 0;
            double yh = 0;
            double y = 0;
            double d = 0;
            double lgm = 0;
            double dithresh = 0;
            int i = 0;
            int dir = 0;
            double tmp = 0;

            igammaepsilon = 0.000000000000001;
            iinvgammabignumber = 4503599627370496.0;
            x0 = iinvgammabignumber;
            yl = 0;
            x1 = 0;
            yh = 1;
            dithresh = 5*igammaepsilon;
            d = 1/(9*a);
            y = 1-d-normaldistr.invnormaldistribution(y0, _params)*Math.Sqrt(d);
            x = a*y*y*y;
            lgm = gammafunc.lngamma(a, ref tmp, _params);
            i = 0;
            while( i<10 )
            {
                if( (double)(x)>(double)(x0) || (double)(x)<(double)(x1) )
                {
                    d = 0.0625;
                    break;
                }
                y = incompletegammac(a, x, _params);
                if( (double)(y)<(double)(yl) || (double)(y)>(double)(yh) )
                {
                    d = 0.0625;
                    break;
                }
                if( (double)(y)<(double)(y0) )
                {
                    x0 = x;
                    yl = y;
                }
                else
                {
                    x1 = x;
                    yh = y;
                }
                d = (a-1)*Math.Log(x)-x-lgm;
                if( (double)(d)<(double)(-709.78271289338399) )
                {
                    d = 0.0625;
                    break;
                }
                d = -Math.Exp(d);
                d = (y-y0)/d;
                if( (double)(Math.Abs(d/x))<(double)(igammaepsilon) )
                {
                    result = x;
                    return result;
                }
                x = x-d;
                i = i+1;
            }
            if( (double)(x0)==(double)(iinvgammabignumber) )
            {
                if( (double)(x)<=(double)(0) )
                {
                    x = 1;
                }
                while( (double)(x0)==(double)(iinvgammabignumber) )
                {
                    x = (1+d)*x;
                    y = incompletegammac(a, x, _params);
                    if( (double)(y)<(double)(y0) )
                    {
                        x0 = x;
                        yl = y;
                        break;
                    }
                    d = d+d;
                }
            }
            d = 0.5;
            dir = 0;
            i = 0;
            while( i<400 )
            {
                x = x1+d*(x0-x1);
                y = incompletegammac(a, x, _params);
                lgm = (x0-x1)/(x1+x0);
                if( (double)(Math.Abs(lgm))<(double)(dithresh) )
                {
                    break;
                }
                lgm = (y-y0)/y0;
                if( (double)(Math.Abs(lgm))<(double)(dithresh) )
                {
                    break;
                }
                if( (double)(x)<=(double)(0.0) )
                {
                    break;
                }
                if( (double)(y)>=(double)(y0) )
                {
                    x1 = x;
                    yh = y;
                    if( dir<0 )
                    {
                        dir = 0;
                        d = 0.5;
                    }
                    else
                    {
                        if( dir>1 )
                        {
                            d = 0.5*d+0.5;
                        }
                        else
                        {
                            d = (y0-yl)/(yh-yl);
                        }
                    }
                    dir = dir+1;
                }
                else
                {
                    x0 = x;
                    yl = y;
                    if( dir>0 )
                    {
                        dir = 0;
                        d = 0.5;
                    }
                    else
                    {
                        if( dir<-1 )
                        {
                            d = 0.5*d;
                        }
                        else
                        {
                            d = (y0-yl)/(yh-yl);
                        }
                    }
                    dir = dir-1;
                }
                i = i+1;
            }
            result = x;
            return result;
        }


    }
    public class chisquaredistr
    {
        /*************************************************************************
        Chi-square distribution

        Returns the area under the left hand tail (from 0 to x)
        of the Chi square probability density function with
        v degrees of freedom.


                                          x
                                           -
                               1          | |  v/2-1  -t/2
         P( x | v )   =   -----------     |   t      e     dt
                           v/2  -       | |
                          2    | (v/2)   -
                                          0

        where x is the Chi-square variable.

        The incomplete gamma integral is used, according to the
        formula

        y = chdtr( v, x ) = igam( v/2.0, x/2.0 ).

        The arguments must both be positive.

        ACCURACY:

        See incomplete gamma function


        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double chisquaredistribution(double v,
            double x,
            alglib.xparams _params)
        {
            double result = 0;

            alglib.ap.assert((double)(x)>=(double)(0) && (double)(v)>=(double)(1), "Domain error in ChiSquareDistribution");
            result = igammaf.incompletegamma(v/2.0, x/2.0, _params);
            return result;
        }


        /*************************************************************************
        Complemented Chi-square distribution

        Returns the area under the right hand tail (from x to
        infinity) of the Chi square probability density function
        with v degrees of freedom:

                                         inf.
                                           -
                               1          | |  v/2-1  -t/2
         P( x | v )   =   -----------     |   t      e     dt
                           v/2  -       | |
                          2    | (v/2)   -
                                          x

        where x is the Chi-square variable.

        The incomplete gamma integral is used, according to the
        formula

        y = chdtr( v, x ) = igamc( v/2.0, x/2.0 ).

        The arguments must both be positive.

        ACCURACY:

        See incomplete gamma function

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double chisquarecdistribution(double v,
            double x,
            alglib.xparams _params)
        {
            double result = 0;

            alglib.ap.assert((double)(x)>=(double)(0) && (double)(v)>=(double)(1), "Domain error in ChiSquareDistributionC");
            result = igammaf.incompletegammac(v/2.0, x/2.0, _params);
            return result;
        }


        /*************************************************************************
        Inverse of complemented Chi-square distribution

        Finds the Chi-square argument x such that the integral
        from x to infinity of the Chi-square density is equal
        to the given cumulative probability y.

        This is accomplished using the inverse gamma integral
        function and the relation

           x/2 = igami( df/2, y );

        ACCURACY:

        See inverse incomplete gamma function


        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double invchisquaredistribution(double v,
            double y,
            alglib.xparams _params)
        {
            double result = 0;

            alglib.ap.assert(((double)(y)>=(double)(0) && (double)(y)<=(double)(1)) && (double)(v)>=(double)(1), "Domain error in InvChiSquareDistribution");
            result = 2*igammaf.invincompletegammac(0.5*v, y, _params);
            return result;
        }


    }
    public class binomialdistr
    {
        /*************************************************************************
        Binomial distribution

        Returns the sum of the terms 0 through k of the Binomial
        probability density:

          k
          --  ( n )   j      n-j
          >   (   )  p  (1-p)
          --  ( j )
         j=0

        The terms are not summed directly; instead the incomplete
        beta integral is employed, according to the formula

        y = bdtr( k, n, p ) = incbet( n-k, k+1, 1-p ).

        The arguments must be positive, with p ranging from 0 to 1.

        ACCURACY:

        Tested at random points (a,b,p), with p between 0 and 1.

                      a,b                     Relative error:
        arithmetic  domain     # trials      peak         rms
         For p between 0.001 and 1:
           IEEE     0,100       100000      4.3e-15     2.6e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double binomialdistribution(int k,
            int n,
            double p,
            alglib.xparams _params)
        {
            double result = 0;
            double dk = 0;
            double dn = 0;

            alglib.ap.assert((double)(p)>=(double)(0) && (double)(p)<=(double)(1), "Domain error in BinomialDistribution");
            alglib.ap.assert(k>=-1 && k<=n, "Domain error in BinomialDistribution");
            if( k==-1 )
            {
                result = 0;
                return result;
            }
            if( k==n )
            {
                result = 1;
                return result;
            }
            dn = n-k;
            if( k==0 )
            {
                dk = Math.Pow(1.0-p, dn);
            }
            else
            {
                dk = k+1;
                dk = ibetaf.incompletebeta(dn, dk, 1.0-p, _params);
            }
            result = dk;
            return result;
        }


        /*************************************************************************
        Complemented binomial distribution

        Returns the sum of the terms k+1 through n of the Binomial
        probability density:

          n
          --  ( n )   j      n-j
          >   (   )  p  (1-p)
          --  ( j )
         j=k+1

        The terms are not summed directly; instead the incomplete
        beta integral is employed, according to the formula

        y = bdtrc( k, n, p ) = incbet( k+1, n-k, p ).

        The arguments must be positive, with p ranging from 0 to 1.

        ACCURACY:

        Tested at random points (a,b,p).

                      a,b                     Relative error:
        arithmetic  domain     # trials      peak         rms
         For p between 0.001 and 1:
           IEEE     0,100       100000      6.7e-15     8.2e-16
         For p between 0 and .001:
           IEEE     0,100       100000      1.5e-13     2.7e-15

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double binomialcdistribution(int k,
            int n,
            double p,
            alglib.xparams _params)
        {
            double result = 0;
            double dk = 0;
            double dn = 0;

            alglib.ap.assert((double)(p)>=(double)(0) && (double)(p)<=(double)(1), "Domain error in BinomialDistributionC");
            alglib.ap.assert(k>=-1 && k<=n, "Domain error in BinomialDistributionC");
            if( k==-1 )
            {
                result = 1;
                return result;
            }
            if( k==n )
            {
                result = 0;
                return result;
            }
            dn = n-k;
            if( k==0 )
            {
                if( (double)(p)<(double)(0.01) )
                {
                    dk = -nearunityunit.nuexpm1(dn*nearunityunit.nulog1p(-p, _params), _params);
                }
                else
                {
                    dk = 1.0-Math.Pow(1.0-p, dn);
                }
            }
            else
            {
                dk = k+1;
                dk = ibetaf.incompletebeta(dk, dn, p, _params);
            }
            result = dk;
            return result;
        }


        /*************************************************************************
        Inverse binomial distribution

        Finds the event probability p such that the sum of the
        terms 0 through k of the Binomial probability density
        is equal to the given cumulative probability y.

        This is accomplished using the inverse beta integral
        function and the relation

        1 - p = incbi( n-k, k+1, y ).

        ACCURACY:

        Tested at random points (a,b,p).

                      a,b                     Relative error:
        arithmetic  domain     # trials      peak         rms
         For p between 0.001 and 1:
           IEEE     0,100       100000      2.3e-14     6.4e-16
           IEEE     0,10000     100000      6.6e-12     1.2e-13
         For p between 10^-6 and 0.001:
           IEEE     0,100       100000      2.0e-12     1.3e-14
           IEEE     0,10000     100000      1.5e-12     3.2e-14

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double invbinomialdistribution(int k,
            int n,
            double y,
            alglib.xparams _params)
        {
            double result = 0;
            double dk = 0;
            double dn = 0;
            double p = 0;

            alglib.ap.assert(k>=0 && k<n, "Domain error in InvBinomialDistribution");
            dn = n-k;
            if( k==0 )
            {
                if( (double)(y)>(double)(0.8) )
                {
                    p = -nearunityunit.nuexpm1(nearunityunit.nulog1p(y-1.0, _params)/dn, _params);
                }
                else
                {
                    p = 1.0-Math.Pow(y, 1.0/dn);
                }
            }
            else
            {
                dk = k+1;
                p = ibetaf.incompletebeta(dn, dk, 0.5, _params);
                if( (double)(p)>(double)(0.5) )
                {
                    p = ibetaf.invincompletebeta(dk, dn, 1.0-y, _params);
                }
                else
                {
                    p = 1.0-ibetaf.invincompletebeta(dn, dk, y, _params);
                }
            }
            result = p;
            return result;
        }


    }
    public class expintegrals
    {
        /*************************************************************************
        Exponential integral Ei(x)

                      x
                       -     t
                      | |   e
           Ei(x) =   -|-   ---  dt .
                    | |     t
                     -
                    -inf

        Not defined for x <= 0.
        See also expn.c.



        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE       0,100       50000      8.6e-16     1.3e-16

        Cephes Math Library Release 2.8:  May, 1999
        Copyright 1999 by Stephen L. Moshier
        *************************************************************************/
        public static double exponentialintegralei(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double eul = 0;
            double f = 0;
            double f1 = 0;
            double f2 = 0;
            double w = 0;

            eul = 0.5772156649015328606065;
            if( (double)(x)<=(double)(0) )
            {
                result = 0;
                return result;
            }
            if( (double)(x)<(double)(2) )
            {
                f1 = -5.350447357812542947283;
                f1 = f1*x+218.5049168816613393830;
                f1 = f1*x-4176.572384826693777058;
                f1 = f1*x+55411.76756393557601232;
                f1 = f1*x-331338.1331178144034309;
                f1 = f1*x+1592627.163384945414220;
                f2 = 1.000000000000000000000;
                f2 = f2*x-52.50547959112862969197;
                f2 = f2*x+1259.616186786790571525;
                f2 = f2*x-17565.49581973534652631;
                f2 = f2*x+149306.2117002725991967;
                f2 = f2*x-729494.9239640527645655;
                f2 = f2*x+1592627.163384945429726;
                f = f1/f2;
                result = eul+Math.Log(x)+x*f;
                return result;
            }
            if( (double)(x)<(double)(4) )
            {
                w = 1/x;
                f1 = 1.981808503259689673238E-2;
                f1 = f1*w-1.271645625984917501326;
                f1 = f1*w-2.088160335681228318920;
                f1 = f1*w+2.755544509187936721172;
                f1 = f1*w-4.409507048701600257171E-1;
                f1 = f1*w+4.665623805935891391017E-2;
                f1 = f1*w-1.545042679673485262580E-3;
                f1 = f1*w+7.059980605299617478514E-5;
                f2 = 1.000000000000000000000;
                f2 = f2*w+1.476498670914921440652;
                f2 = f2*w+5.629177174822436244827E-1;
                f2 = f2*w+1.699017897879307263248E-1;
                f2 = f2*w+2.291647179034212017463E-2;
                f2 = f2*w+4.450150439728752875043E-3;
                f2 = f2*w+1.727439612206521482874E-4;
                f2 = f2*w+3.953167195549672482304E-5;
                f = f1/f2;
                result = Math.Exp(x)*w*(1+w*f);
                return result;
            }
            if( (double)(x)<(double)(8) )
            {
                w = 1/x;
                f1 = -1.373215375871208729803;
                f1 = f1*w-7.084559133740838761406E-1;
                f1 = f1*w+1.580806855547941010501;
                f1 = f1*w-2.601500427425622944234E-1;
                f1 = f1*w+2.994674694113713763365E-2;
                f1 = f1*w-1.038086040188744005513E-3;
                f1 = f1*w+4.371064420753005429514E-5;
                f1 = f1*w+2.141783679522602903795E-6;
                f2 = 1.000000000000000000000;
                f2 = f2*w+8.585231423622028380768E-1;
                f2 = f2*w+4.483285822873995129957E-1;
                f2 = f2*w+7.687932158124475434091E-2;
                f2 = f2*w+2.449868241021887685904E-2;
                f2 = f2*w+8.832165941927796567926E-4;
                f2 = f2*w+4.590952299511353531215E-4;
                f2 = f2*w+-4.729848351866523044863E-6;
                f2 = f2*w+2.665195537390710170105E-6;
                f = f1/f2;
                result = Math.Exp(x)*w*(1+w*f);
                return result;
            }
            if( (double)(x)<(double)(16) )
            {
                w = 1/x;
                f1 = -2.106934601691916512584;
                f1 = f1*w+1.732733869664688041885;
                f1 = f1*w-2.423619178935841904839E-1;
                f1 = f1*w+2.322724180937565842585E-2;
                f1 = f1*w+2.372880440493179832059E-4;
                f1 = f1*w-8.343219561192552752335E-5;
                f1 = f1*w+1.363408795605250394881E-5;
                f1 = f1*w-3.655412321999253963714E-7;
                f1 = f1*w+1.464941733975961318456E-8;
                f1 = f1*w+6.176407863710360207074E-10;
                f2 = 1.000000000000000000000;
                f2 = f2*w-2.298062239901678075778E-1;
                f2 = f2*w+1.105077041474037862347E-1;
                f2 = f2*w-1.566542966630792353556E-2;
                f2 = f2*w+2.761106850817352773874E-3;
                f2 = f2*w-2.089148012284048449115E-4;
                f2 = f2*w+1.708528938807675304186E-5;
                f2 = f2*w-4.459311796356686423199E-7;
                f2 = f2*w+1.394634930353847498145E-8;
                f2 = f2*w+6.150865933977338354138E-10;
                f = f1/f2;
                result = Math.Exp(x)*w*(1+w*f);
                return result;
            }
            if( (double)(x)<(double)(32) )
            {
                w = 1/x;
                f1 = -2.458119367674020323359E-1;
                f1 = f1*w-1.483382253322077687183E-1;
                f1 = f1*w+7.248291795735551591813E-2;
                f1 = f1*w-1.348315687380940523823E-2;
                f1 = f1*w+1.342775069788636972294E-3;
                f1 = f1*w-7.942465637159712264564E-5;
                f1 = f1*w+2.644179518984235952241E-6;
                f1 = f1*w-4.239473659313765177195E-8;
                f2 = 1.000000000000000000000;
                f2 = f2*w-1.044225908443871106315E-1;
                f2 = f2*w-2.676453128101402655055E-1;
                f2 = f2*w+9.695000254621984627876E-2;
                f2 = f2*w-1.601745692712991078208E-2;
                f2 = f2*w+1.496414899205908021882E-3;
                f2 = f2*w-8.462452563778485013756E-5;
                f2 = f2*w+2.728938403476726394024E-6;
                f2 = f2*w-4.239462431819542051337E-8;
                f = f1/f2;
                result = Math.Exp(x)*w*(1+w*f);
                return result;
            }
            if( (double)(x)<(double)(64) )
            {
                w = 1/x;
                f1 = 1.212561118105456670844E-1;
                f1 = f1*w-5.823133179043894485122E-1;
                f1 = f1*w+2.348887314557016779211E-1;
                f1 = f1*w-3.040034318113248237280E-2;
                f1 = f1*w+1.510082146865190661777E-3;
                f1 = f1*w-2.523137095499571377122E-5;
                f2 = 1.000000000000000000000;
                f2 = f2*w-1.002252150365854016662;
                f2 = f2*w+2.928709694872224144953E-1;
                f2 = f2*w-3.337004338674007801307E-2;
                f2 = f2*w+1.560544881127388842819E-3;
                f2 = f2*w-2.523137093603234562648E-5;
                f = f1/f2;
                result = Math.Exp(x)*w*(1+w*f);
                return result;
            }
            w = 1/x;
            f1 = -7.657847078286127362028E-1;
            f1 = f1*w+6.886192415566705051750E-1;
            f1 = f1*w-2.132598113545206124553E-1;
            f1 = f1*w+3.346107552384193813594E-2;
            f1 = f1*w-3.076541477344756050249E-3;
            f1 = f1*w+1.747119316454907477380E-4;
            f1 = f1*w-6.103711682274170530369E-6;
            f1 = f1*w+1.218032765428652199087E-7;
            f1 = f1*w-1.086076102793290233007E-9;
            f2 = 1.000000000000000000000;
            f2 = f2*w-1.888802868662308731041;
            f2 = f2*w+1.066691687211408896850;
            f2 = f2*w-2.751915982306380647738E-1;
            f2 = f2*w+3.930852688233823569726E-2;
            f2 = f2*w-3.414684558602365085394E-3;
            f2 = f2*w+1.866844370703555398195E-4;
            f2 = f2*w-6.345146083130515357861E-6;
            f2 = f2*w+1.239754287483206878024E-7;
            f2 = f2*w-1.086076102793126632978E-9;
            f = f1/f2;
            result = Math.Exp(x)*w*(1+w*f);
            return result;
        }


        /*************************************************************************
        Exponential integral En(x)

        Evaluates the exponential integral

                        inf.
                          -
                         | |   -xt
                         |    e
             E (x)  =    |    ----  dt.
              n          |      n
                       | |     t
                        -
                         1


        Both n and x must be nonnegative.

        The routine employs either a power series, a continued
        fraction, or an asymptotic formula depending on the
        relative values of n and x.

        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE      0, 30       10000       1.7e-15     3.6e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1985, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double exponentialintegralen(double x,
            int n,
            alglib.xparams _params)
        {
            double result = 0;
            double r = 0;
            double t = 0;
            double yk = 0;
            double xk = 0;
            double pk = 0;
            double pkm1 = 0;
            double pkm2 = 0;
            double qk = 0;
            double qkm1 = 0;
            double qkm2 = 0;
            double psi = 0;
            double z = 0;
            int i = 0;
            int k = 0;
            double big = 0;
            double eul = 0;

            eul = 0.57721566490153286060;
            big = 1.44115188075855872*Math.Pow(10, 17);
            if( ((n<0 || (double)(x)<(double)(0)) || (double)(x)>(double)(170)) || ((double)(x)==(double)(0) && n<2) )
            {
                result = -1;
                return result;
            }
            if( (double)(x)==(double)(0) )
            {
                result = (double)1/(double)(n-1);
                return result;
            }
            if( n==0 )
            {
                result = Math.Exp(-x)/x;
                return result;
            }
            if( n>5000 )
            {
                xk = x+n;
                yk = 1/(xk*xk);
                t = n;
                result = yk*t*(6*x*x-8*t*x+t*t);
                result = yk*(result+t*(t-2.0*x));
                result = yk*(result+t);
                result = (result+1)*Math.Exp(-x)/xk;
                return result;
            }
            if( (double)(x)<=(double)(1) )
            {
                psi = -eul-Math.Log(x);
                for(i=1; i<=n-1; i++)
                {
                    psi = psi+(double)1/(double)i;
                }
                z = -x;
                xk = 0;
                yk = 1;
                pk = 1-n;
                if( n==1 )
                {
                    result = 0.0;
                }
                else
                {
                    result = 1.0/pk;
                }
                do
                {
                    xk = xk+1;
                    yk = yk*z/xk;
                    pk = pk+1;
                    if( (double)(pk)!=(double)(0) )
                    {
                        result = result+yk/pk;
                    }
                    if( (double)(result)!=(double)(0) )
                    {
                        t = Math.Abs(yk/result);
                    }
                    else
                    {
                        t = 1;
                    }
                }
                while( (double)(t)>=(double)(math.machineepsilon) );
                t = 1;
                for(i=1; i<=n-1; i++)
                {
                    t = t*z/i;
                }
                result = psi*t-result;
                return result;
            }
            else
            {
                k = 1;
                pkm2 = 1;
                qkm2 = x;
                pkm1 = 1.0;
                qkm1 = x+n;
                result = pkm1/qkm1;
                do
                {
                    k = k+1;
                    if( k%2==1 )
                    {
                        yk = 1;
                        xk = n+(double)(k-1)/(double)2;
                    }
                    else
                    {
                        yk = x;
                        xk = (double)k/(double)2;
                    }
                    pk = pkm1*yk+pkm2*xk;
                    qk = qkm1*yk+qkm2*xk;
                    if( (double)(qk)!=(double)(0) )
                    {
                        r = pk/qk;
                        t = Math.Abs((result-r)/r);
                        result = r;
                    }
                    else
                    {
                        t = 1;
                    }
                    pkm2 = pkm1;
                    pkm1 = pk;
                    qkm2 = qkm1;
                    qkm1 = qk;
                    if( (double)(Math.Abs(pk))>(double)(big) )
                    {
                        pkm2 = pkm2/big;
                        pkm1 = pkm1/big;
                        qkm2 = qkm2/big;
                        qkm1 = qkm1/big;
                    }
                }
                while( (double)(t)>=(double)(math.machineepsilon) );
                result = result*Math.Exp(-x);
            }
            return result;
        }


    }
    public class jacobianelliptic
    {
        /*************************************************************************
        Jacobian Elliptic Functions

        Evaluates the Jacobian elliptic functions sn(u|m), cn(u|m),
        and dn(u|m) of parameter m between 0 and 1, and real
        argument u.

        These functions are periodic, with quarter-period on the
        real axis equal to the complete elliptic integral
        ellpk(1.0-m).

        Relation to incomplete elliptic integral:
        If u = ellik(phi,m), then sn(u|m) = sin(phi),
        and cn(u|m) = cos(phi).  Phi is called the amplitude of u.

        Computation is by means of the arithmetic-geometric mean
        algorithm, except when m is within 1e-9 of 0 or 1.  In the
        latter case with m close to 1, the approximation applies
        only for phi < pi/2.

        ACCURACY:

        Tested at random points with u between 0 and 10, m between
        0 and 1.

                   Absolute error (* = relative error):
        arithmetic   function   # trials      peak         rms
           IEEE      phi         10000       9.2e-16*    1.4e-16*
           IEEE      sn          50000       4.1e-15     4.6e-16
           IEEE      cn          40000       3.6e-15     4.4e-16
           IEEE      dn          10000       1.3e-12     1.8e-14

         Peak error observed in consistency check using addition
        theorem for sn(u+v) was 4e-16 (absolute).  Also tested by
        the above relation to the incomplete elliptic integral.
        Accuracy deteriorates when u is large.

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static void jacobianellipticfunctions(double u,
            double m,
            ref double sn,
            ref double cn,
            ref double dn,
            ref double ph,
            alglib.xparams _params)
        {
            double ai = 0;
            double b = 0;
            double phi = 0;
            double t = 0;
            double twon = 0;
            double[] a = new double[0];
            double[] c = new double[0];
            int i = 0;

            sn = 0;
            cn = 0;
            dn = 0;
            ph = 0;

            alglib.ap.assert((double)(m)>=(double)(0) && (double)(m)<=(double)(1), "Domain error in JacobianEllipticFunctions: m<0 or m>1");
            a = new double[8+1];
            c = new double[8+1];
            if( (double)(m)<(double)(1.0e-9) )
            {
                t = Math.Sin(u);
                b = Math.Cos(u);
                ai = 0.25*m*(u-t*b);
                sn = t-ai*b;
                cn = b+ai*t;
                ph = u-ai;
                dn = 1.0-0.5*m*t*t;
                return;
            }
            if( (double)(m)>=(double)(0.9999999999) )
            {
                ai = 0.25*(1.0-m);
                b = Math.Cosh(u);
                t = Math.Tanh(u);
                phi = 1.0/b;
                twon = b*Math.Sinh(u);
                sn = t+ai*(twon-u)/(b*b);
                ph = 2.0*Math.Atan(Math.Exp(u))-1.57079632679489661923+ai*(twon-u)/b;
                ai = ai*t*phi;
                cn = phi-ai*(twon-u);
                dn = phi+ai*(twon+u);
                return;
            }
            a[0] = 1.0;
            b = Math.Sqrt(1.0-m);
            c[0] = Math.Sqrt(m);
            twon = 1.0;
            i = 0;
            while( (double)(Math.Abs(c[i]/a[i]))>(double)(math.machineepsilon) )
            {
                if( i>7 )
                {
                    alglib.ap.assert(false, "Overflow in JacobianEllipticFunctions");
                    break;
                }
                ai = a[i];
                i = i+1;
                c[i] = 0.5*(ai-b);
                t = Math.Sqrt(ai*b);
                a[i] = 0.5*(ai+b);
                b = t;
                twon = twon*2.0;
            }
            phi = twon*a[i]*u;
            do
            {
                t = c[i]*Math.Sin(phi)/a[i];
                b = phi;
                phi = (Math.Asin(t)+phi)/2.0;
                i = i-1;
            }
            while( i!=0 );
            sn = Math.Sin(phi);
            t = Math.Cos(phi);
            cn = t;
            dn = t/Math.Cos(phi-b);
            ph = phi;
        }


    }
    public class trigintegrals
    {
        /*************************************************************************
        Sine and cosine integrals

        Evaluates the integrals

                                 x
                                 -
                                |  cos t - 1
          Ci(x) = eul + ln x +  |  --------- dt,
                                |      t
                               -
                                0
                    x
                    -
                   |  sin t
          Si(x) =  |  ----- dt
                   |    t
                  -
                   0

        where eul = 0.57721566490153286061 is Euler's constant.
        The integrals are approximated by rational functions.
        For x > 8 auxiliary functions f(x) and g(x) are employed
        such that

        Ci(x) = f(x) sin(x) - g(x) cos(x)
        Si(x) = pi/2 - f(x) cos(x) - g(x) sin(x)


        ACCURACY:
           Test interval = [0,50].
        Absolute error, except relative when > 1:
        arithmetic   function   # trials      peak         rms
           IEEE        Si        30000       4.4e-16     7.3e-17
           IEEE        Ci        30000       6.9e-16     5.1e-17

        Cephes Math Library Release 2.1:  January, 1989
        Copyright 1984, 1987, 1989 by Stephen L. Moshier
        *************************************************************************/
        public static void sinecosineintegrals(double x,
            ref double si,
            ref double ci,
            alglib.xparams _params)
        {
            double z = 0;
            double c = 0;
            double s = 0;
            double f = 0;
            double g = 0;
            int sg = 0;
            double sn = 0;
            double sd = 0;
            double cn = 0;
            double cd = 0;
            double fn = 0;
            double fd = 0;
            double gn = 0;
            double gd = 0;

            si = 0;
            ci = 0;

            if( (double)(x)<(double)(0) )
            {
                sg = -1;
                x = -x;
            }
            else
            {
                sg = 0;
            }
            if( (double)(x)==(double)(0) )
            {
                si = 0;
                ci = -math.maxrealnumber;
                return;
            }
            if( (double)(x)>(double)(1.0E9) )
            {
                si = 1.570796326794896619-Math.Cos(x)/x;
                ci = Math.Sin(x)/x;
                return;
            }
            if( (double)(x)<=(double)(4) )
            {
                z = x*x;
                sn = -8.39167827910303881427E-11;
                sn = sn*z+4.62591714427012837309E-8;
                sn = sn*z-9.75759303843632795789E-6;
                sn = sn*z+9.76945438170435310816E-4;
                sn = sn*z-4.13470316229406538752E-2;
                sn = sn*z+1.00000000000000000302E0;
                sd = 2.03269266195951942049E-12;
                sd = sd*z+1.27997891179943299903E-9;
                sd = sd*z+4.41827842801218905784E-7;
                sd = sd*z+9.96412122043875552487E-5;
                sd = sd*z+1.42085239326149893930E-2;
                sd = sd*z+9.99999999999999996984E-1;
                s = x*sn/sd;
                cn = 2.02524002389102268789E-11;
                cn = cn*z-1.35249504915790756375E-8;
                cn = cn*z+3.59325051419993077021E-6;
                cn = cn*z-4.74007206873407909465E-4;
                cn = cn*z+2.89159652607555242092E-2;
                cn = cn*z-1.00000000000000000080E0;
                cd = 4.07746040061880559506E-12;
                cd = cd*z+3.06780997581887812692E-9;
                cd = cd*z+1.23210355685883423679E-6;
                cd = cd*z+3.17442024775032769882E-4;
                cd = cd*z+5.10028056236446052392E-2;
                cd = cd*z+4.00000000000000000080E0;
                c = z*cn/cd;
                if( sg!=0 )
                {
                    s = -s;
                }
                si = s;
                ci = 0.57721566490153286061+Math.Log(x)+c;
                return;
            }
            s = Math.Sin(x);
            c = Math.Cos(x);
            z = 1.0/(x*x);
            if( (double)(x)<(double)(8) )
            {
                fn = 4.23612862892216586994E0;
                fn = fn*z+5.45937717161812843388E0;
                fn = fn*z+1.62083287701538329132E0;
                fn = fn*z+1.67006611831323023771E-1;
                fn = fn*z+6.81020132472518137426E-3;
                fn = fn*z+1.08936580650328664411E-4;
                fn = fn*z+5.48900223421373614008E-7;
                fd = 1.00000000000000000000E0;
                fd = fd*z+8.16496634205391016773E0;
                fd = fd*z+7.30828822505564552187E0;
                fd = fd*z+1.86792257950184183883E0;
                fd = fd*z+1.78792052963149907262E-1;
                fd = fd*z+7.01710668322789753610E-3;
                fd = fd*z+1.10034357153915731354E-4;
                fd = fd*z+5.48900252756255700982E-7;
                f = fn/(x*fd);
                gn = 8.71001698973114191777E-2;
                gn = gn*z+6.11379109952219284151E-1;
                gn = gn*z+3.97180296392337498885E-1;
                gn = gn*z+7.48527737628469092119E-2;
                gn = gn*z+5.38868681462177273157E-3;
                gn = gn*z+1.61999794598934024525E-4;
                gn = gn*z+1.97963874140963632189E-6;
                gn = gn*z+7.82579040744090311069E-9;
                gd = 1.00000000000000000000E0;
                gd = gd*z+1.64402202413355338886E0;
                gd = gd*z+6.66296701268987968381E-1;
                gd = gd*z+9.88771761277688796203E-2;
                gd = gd*z+6.22396345441768420760E-3;
                gd = gd*z+1.73221081474177119497E-4;
                gd = gd*z+2.02659182086343991969E-6;
                gd = gd*z+7.82579218933534490868E-9;
                g = z*gn/gd;
            }
            else
            {
                fn = 4.55880873470465315206E-1;
                fn = fn*z+7.13715274100146711374E-1;
                fn = fn*z+1.60300158222319456320E-1;
                fn = fn*z+1.16064229408124407915E-2;
                fn = fn*z+3.49556442447859055605E-4;
                fn = fn*z+4.86215430826454749482E-6;
                fn = fn*z+3.20092790091004902806E-8;
                fn = fn*z+9.41779576128512936592E-11;
                fn = fn*z+9.70507110881952024631E-14;
                fd = 1.00000000000000000000E0;
                fd = fd*z+9.17463611873684053703E-1;
                fd = fd*z+1.78685545332074536321E-1;
                fd = fd*z+1.22253594771971293032E-2;
                fd = fd*z+3.58696481881851580297E-4;
                fd = fd*z+4.92435064317881464393E-6;
                fd = fd*z+3.21956939101046018377E-8;
                fd = fd*z+9.43720590350276732376E-11;
                fd = fd*z+9.70507110881952025725E-14;
                f = fn/(x*fd);
                gn = 6.97359953443276214934E-1;
                gn = gn*z+3.30410979305632063225E-1;
                gn = gn*z+3.84878767649974295920E-2;
                gn = gn*z+1.71718239052347903558E-3;
                gn = gn*z+3.48941165502279436777E-5;
                gn = gn*z+3.47131167084116673800E-7;
                gn = gn*z+1.70404452782044526189E-9;
                gn = gn*z+3.85945925430276600453E-12;
                gn = gn*z+3.14040098946363334640E-15;
                gd = 1.00000000000000000000E0;
                gd = gd*z+1.68548898811011640017E0;
                gd = gd*z+4.87852258695304967486E-1;
                gd = gd*z+4.67913194259625806320E-2;
                gd = gd*z+1.90284426674399523638E-3;
                gd = gd*z+3.68475504442561108162E-5;
                gd = gd*z+3.57043223443740838771E-7;
                gd = gd*z+1.72693748966316146736E-9;
                gd = gd*z+3.87830166023954706752E-12;
                gd = gd*z+3.14040098946363335242E-15;
                g = z*gn/gd;
            }
            si = 1.570796326794896619-f*c-g*s;
            if( sg!=0 )
            {
                si = -si;
            }
            ci = f*s-g*c;
        }


        /*************************************************************************
        Hyperbolic sine and cosine integrals

        Approximates the integrals

                                   x
                                   -
                                  | |   cosh t - 1
          Chi(x) = eul + ln x +   |    -----------  dt,
                                | |          t
                                 -
                                 0

                      x
                      -
                     | |  sinh t
          Shi(x) =   |    ------  dt
                   | |       t
                    -
                    0

        where eul = 0.57721566490153286061 is Euler's constant.
        The integrals are evaluated by power series for x < 8
        and by Chebyshev expansions for x between 8 and 88.
        For large x, both functions approach exp(x)/2x.
        Arguments greater than 88 in magnitude return MAXNUM.


        ACCURACY:

        Test interval 0 to 88.
                             Relative error:
        arithmetic   function  # trials      peak         rms
           IEEE         Shi      30000       6.9e-16     1.6e-16
               Absolute error, except relative when |Chi| > 1:
           IEEE         Chi      30000       8.4e-16     1.4e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static void hyperbolicsinecosineintegrals(double x,
            ref double shi,
            ref double chi,
            alglib.xparams _params)
        {
            double k = 0;
            double z = 0;
            double c = 0;
            double s = 0;
            double a = 0;
            int sg = 0;
            double b0 = 0;
            double b1 = 0;
            double b2 = 0;

            shi = 0;
            chi = 0;

            if( (double)(x)<(double)(0) )
            {
                sg = -1;
                x = -x;
            }
            else
            {
                sg = 0;
            }
            if( (double)(x)==(double)(0) )
            {
                shi = 0;
                chi = -math.maxrealnumber;
                return;
            }
            if( (double)(x)<(double)(8.0) )
            {
                z = x*x;
                a = 1.0;
                s = 1.0;
                c = 0.0;
                k = 2.0;
                do
                {
                    a = a*z/k;
                    c = c+a/k;
                    k = k+1.0;
                    a = a/k;
                    s = s+a/k;
                    k = k+1.0;
                }
                while( (double)(Math.Abs(a/s))>=(double)(math.machineepsilon) );
                s = s*x;
            }
            else
            {
                if( (double)(x)<(double)(18.0) )
                {
                    a = (576.0/x-52.0)/10.0;
                    k = Math.Exp(x)/x;
                    b0 = 1.83889230173399459482E-17;
                    b1 = 0.0;
                    chebiterationshichi(a, -9.55485532279655569575E-17, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 2.04326105980879882648E-16, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 1.09896949074905343022E-15, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -1.31313534344092599234E-14, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 5.93976226264314278932E-14, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -3.47197010497749154755E-14, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -1.40059764613117131000E-12, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 9.49044626224223543299E-12, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -1.61596181145435454033E-11, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -1.77899784436430310321E-10, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 1.35455469767246947469E-9, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -1.03257121792819495123E-9, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -3.56699611114982536845E-8, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 1.44818877384267342057E-7, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 7.82018215184051295296E-7, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -5.39919118403805073710E-6, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -3.12458202168959833422E-5, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 8.90136741950727517826E-5, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 2.02558474743846862168E-3, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 2.96064440855633256972E-2, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 1.11847751047257036625E0, ref b0, ref b1, ref b2, _params);
                    s = k*0.5*(b0-b2);
                    b0 = -8.12435385225864036372E-18;
                    b1 = 0.0;
                    chebiterationshichi(a, 2.17586413290339214377E-17, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 5.22624394924072204667E-17, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -9.48812110591690559363E-16, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 5.35546311647465209166E-15, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -1.21009970113732918701E-14, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -6.00865178553447437951E-14, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 7.16339649156028587775E-13, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -2.93496072607599856104E-12, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -1.40359438136491256904E-12, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 8.76302288609054966081E-11, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -4.40092476213282340617E-10, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -1.87992075640569295479E-10, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 1.31458150989474594064E-8, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -4.75513930924765465590E-8, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -2.21775018801848880741E-7, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 1.94635531373272490962E-6, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 4.33505889257316408893E-6, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -6.13387001076494349496E-5, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, -3.13085477492997465138E-4, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 4.97164789823116062801E-4, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 2.64347496031374526641E-2, ref b0, ref b1, ref b2, _params);
                    chebiterationshichi(a, 1.11446150876699213025E0, ref b0, ref b1, ref b2, _params);
                    c = k*0.5*(b0-b2);
                }
                else
                {
                    if( (double)(x)<=(double)(88.0) )
                    {
                        a = (6336.0/x-212.0)/70.0;
                        k = Math.Exp(x)/x;
                        b0 = -1.05311574154850938805E-17;
                        b1 = 0.0;
                        chebiterationshichi(a, 2.62446095596355225821E-17, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 8.82090135625368160657E-17, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -3.38459811878103047136E-16, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -8.30608026366935789136E-16, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 3.93397875437050071776E-15, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.01765565969729044505E-14, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -4.21128170307640802703E-14, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -1.60818204519802480035E-13, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 3.34714954175994481761E-13, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 2.72600352129153073807E-12, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.66894954752839083608E-12, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -3.49278141024730899554E-11, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -1.58580661666482709598E-10, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -1.79289437183355633342E-10, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.76281629144264523277E-9, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.69050228879421288846E-8, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.25391771228487041649E-7, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.16229947068677338732E-6, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.61038260117376323993E-5, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 3.49810375601053973070E-4, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.28478065259647610779E-2, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.03665722588798326712E0, ref b0, ref b1, ref b2, _params);
                        s = k*0.5*(b0-b2);
                        b0 = 8.06913408255155572081E-18;
                        b1 = 0.0;
                        chebiterationshichi(a, -2.08074168180148170312E-17, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -5.98111329658272336816E-17, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 2.68533951085945765591E-16, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 4.52313941698904694774E-16, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -3.10734917335299464535E-15, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -4.42823207332531972288E-15, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 3.49639695410806959872E-14, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 6.63406731718911586609E-14, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -3.71902448093119218395E-13, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -1.27135418132338309016E-12, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 2.74851141935315395333E-12, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 2.33781843985453438400E-11, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 2.71436006377612442764E-11, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -2.56600180000355990529E-10, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -1.61021375163803438552E-9, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -4.72543064876271773512E-9, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, -3.00095178028681682282E-9, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 7.79387474390914922337E-8, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.06942765566401507066E-6, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.59503164802313196374E-5, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 3.49592575153777996871E-4, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.28475387530065247392E-2, ref b0, ref b1, ref b2, _params);
                        chebiterationshichi(a, 1.03665693917934275131E0, ref b0, ref b1, ref b2, _params);
                        c = k*0.5*(b0-b2);
                    }
                    else
                    {
                        if( sg!=0 )
                        {
                            shi = -math.maxrealnumber;
                        }
                        else
                        {
                            shi = math.maxrealnumber;
                        }
                        chi = math.maxrealnumber;
                        return;
                    }
                }
            }
            if( sg!=0 )
            {
                s = -s;
            }
            shi = s;
            chi = 0.57721566490153286061+Math.Log(x)+c;
        }


        private static void chebiterationshichi(double x,
            double c,
            ref double b0,
            ref double b1,
            ref double b2,
            alglib.xparams _params)
        {
            b2 = b1;
            b1 = b0;
            b0 = x*b1-b2+c;
        }


    }
    public class chebyshev
    {
        /*************************************************************************
        Calculation of the value of the Chebyshev polynomials of the
        first and second kinds.

        Parameters:
            r   -   polynomial kind, either 1 or 2.
            n   -   degree, n>=0
            x   -   argument, -1 <= x <= 1

        Result:
            the value of the Chebyshev polynomial at x
        *************************************************************************/
        public static double chebyshevcalculate(int r,
            int n,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            int i = 0;
            double a = 0;
            double b = 0;

            result = 0;
            
            //
            // Prepare A and B
            //
            if( r==1 )
            {
                a = 1;
                b = x;
            }
            else
            {
                a = 1;
                b = 2*x;
            }
            
            //
            // Special cases: N=0 or N=1
            //
            if( n==0 )
            {
                result = a;
                return result;
            }
            if( n==1 )
            {
                result = b;
                return result;
            }
            
            //
            // General case: N>=2
            //
            for(i=2; i<=n; i++)
            {
                result = 2*x*b-a;
                a = b;
                b = result;
            }
            return result;
        }


        /*************************************************************************
        Summation of Chebyshev polynomials using Clenshaw's recurrence formula.

        This routine calculates
            c[0]*T0(x) + c[1]*T1(x) + ... + c[N]*TN(x)
        or
            c[0]*U0(x) + c[1]*U1(x) + ... + c[N]*UN(x)
        depending on the R.

        Parameters:
            r   -   polynomial kind, either 1 or 2.
            n   -   degree, n>=0
            x   -   argument

        Result:
            the value of the Chebyshev polynomial at x
        *************************************************************************/
        public static double chebyshevsum(double[] c,
            int r,
            int n,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double b1 = 0;
            double b2 = 0;
            int i = 0;

            b1 = 0;
            b2 = 0;
            for(i=n; i>=1; i--)
            {
                result = 2*x*b1-b2+c[i];
                b2 = b1;
                b1 = result;
            }
            if( r==1 )
            {
                result = -b2+x*b1+c[0];
            }
            else
            {
                result = -b2+2*x*b1+c[0];
            }
            return result;
        }


        /*************************************************************************
        Representation of Tn as C[0] + C[1]*X + ... + C[N]*X^N

        Input parameters:
            N   -   polynomial degree, n>=0

        Output parameters:
            C   -   coefficients
        *************************************************************************/
        public static void chebyshevcoefficients(int n,
            ref double[] c,
            alglib.xparams _params)
        {
            int i = 0;

            c = new double[0];

            c = new double[n+1];
            for(i=0; i<=n; i++)
            {
                c[i] = 0;
            }
            if( n==0 || n==1 )
            {
                c[n] = 1;
            }
            else
            {
                c[n] = Math.Exp((n-1)*Math.Log(2));
                for(i=0; i<=n/2-1; i++)
                {
                    c[n-2*(i+1)] = -(c[n-2*i]*(n-2*i)*(n-2*i-1)/4/(i+1)/(n-i-1));
                }
            }
        }


        /*************************************************************************
        Conversion of a series of Chebyshev polynomials to a power series.

        Represents A[0]*T0(x) + A[1]*T1(x) + ... + A[N]*Tn(x) as
        B[0] + B[1]*X + ... + B[N]*X^N.

        Input parameters:
            A   -   Chebyshev series coefficients
            N   -   degree, N>=0
            
        Output parameters
            B   -   power series coefficients
        *************************************************************************/
        public static void fromchebyshev(double[] a,
            int n,
            ref double[] b,
            alglib.xparams _params)
        {
            int i = 0;
            int k = 0;
            double e = 0;
            double d = 0;

            b = new double[0];

            b = new double[n+1];
            for(i=0; i<=n; i++)
            {
                b[i] = 0;
            }
            d = 0;
            i = 0;
            do
            {
                k = i;
                do
                {
                    e = b[k];
                    b[k] = 0;
                    if( i<=1 && k==i )
                    {
                        b[k] = 1;
                    }
                    else
                    {
                        if( i!=0 )
                        {
                            b[k] = 2*d;
                        }
                        if( k>i+1 )
                        {
                            b[k] = b[k]-b[k-2];
                        }
                    }
                    d = e;
                    k = k+1;
                }
                while( k<=n );
                d = b[i];
                e = 0;
                k = i;
                while( k<=n )
                {
                    e = e+b[k]*a[k];
                    k = k+2;
                }
                b[i] = e;
                i = i+1;
            }
            while( i<=n );
        }


    }
    public class poissondistr
    {
        /*************************************************************************
        Poisson distribution

        Returns the sum of the first k+1 terms of the Poisson
        distribution:

          k         j
          --   -m  m
          >   e    --
          --       j!
         j=0

        The terms are not summed directly; instead the incomplete
        gamma integral is employed, according to the relation

        y = pdtr( k, m ) = igamc( k+1, m ).

        The arguments must both be positive.
        ACCURACY:

        See incomplete gamma function

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double poissondistribution(int k,
            double m,
            alglib.xparams _params)
        {
            double result = 0;

            alglib.ap.assert(k>=0 && (double)(m)>(double)(0), "Domain error in PoissonDistribution");
            result = igammaf.incompletegammac(k+1, m, _params);
            return result;
        }


        /*************************************************************************
        Complemented Poisson distribution

        Returns the sum of the terms k+1 to infinity of the Poisson
        distribution:

         inf.       j
          --   -m  m
          >   e    --
          --       j!
         j=k+1

        The terms are not summed directly; instead the incomplete
        gamma integral is employed, according to the formula

        y = pdtrc( k, m ) = igam( k+1, m ).

        The arguments must both be positive.

        ACCURACY:

        See incomplete gamma function

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double poissoncdistribution(int k,
            double m,
            alglib.xparams _params)
        {
            double result = 0;

            alglib.ap.assert(k>=0 && (double)(m)>(double)(0), "Domain error in PoissonDistributionC");
            result = igammaf.incompletegamma(k+1, m, _params);
            return result;
        }


        /*************************************************************************
        Inverse Poisson distribution

        Finds the Poisson variable x such that the integral
        from 0 to x of the Poisson density is equal to the
        given probability y.

        This is accomplished using the inverse gamma integral
        function and the relation

           m = igami( k+1, y ).

        ACCURACY:

        See inverse incomplete gamma function

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1995, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double invpoissondistribution(int k,
            double y,
            alglib.xparams _params)
        {
            double result = 0;

            alglib.ap.assert((k>=0 && (double)(y)>=(double)(0)) && (double)(y)<(double)(1), "Domain error in InvPoissonDistribution");
            result = igammaf.invincompletegammac(k+1, y, _params);
            return result;
        }


    }
    public class betaf
    {
        /*************************************************************************
        Beta function


                          -     -
                         | (a) | (b)
        beta( a, b )  =  -----------.
                            -
                           | (a+b)

        For large arguments the logarithm of the function is
        evaluated using lgam(), then exponentiated.

        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE       0,30       30000       8.1e-14     1.1e-14

        Cephes Math Library Release 2.0:  April, 1987
        Copyright 1984, 1987 by Stephen L. Moshier
        *************************************************************************/
        public static double beta(double a,
            double b,
            alglib.xparams _params)
        {
            double result = 0;
            double y = 0;
            double sg = 0;
            double s = 0;

            sg = 1;
            alglib.ap.assert((double)(a)>(double)(0) || (double)(a)!=(double)((int)Math.Floor(a)), "Overflow in Beta");
            alglib.ap.assert((double)(b)>(double)(0) || (double)(b)!=(double)((int)Math.Floor(b)), "Overflow in Beta");
            y = a+b;
            if( (double)(Math.Abs(y))>(double)(171.624376956302725) )
            {
                y = gammafunc.lngamma(y, ref s, _params);
                sg = sg*s;
                y = gammafunc.lngamma(b, ref s, _params)-y;
                sg = sg*s;
                y = gammafunc.lngamma(a, ref s, _params)+y;
                sg = sg*s;
                alglib.ap.assert((double)(y)<=(double)(Math.Log(math.maxrealnumber)), "Overflow in Beta");
                result = sg*Math.Exp(y);
                return result;
            }
            y = gammafunc.gammafunction(y, _params);
            alglib.ap.assert((double)(y)!=(double)(0), "Overflow in Beta");
            if( (double)(a)>(double)(b) )
            {
                y = gammafunc.gammafunction(a, _params)/y;
                y = y*gammafunc.gammafunction(b, _params);
            }
            else
            {
                y = gammafunc.gammafunction(b, _params)/y;
                y = y*gammafunc.gammafunction(a, _params);
            }
            result = y;
            return result;
        }


    }
    public class fresnel
    {
        /*************************************************************************
        Fresnel integral

        Evaluates the Fresnel integrals

                  x
                  -
                 | |
        C(x) =   |   cos(pi/2 t**2) dt,
               | |
                -
                 0

                  x
                  -
                 | |
        S(x) =   |   sin(pi/2 t**2) dt.
               | |
                -
                 0


        The integrals are evaluated by a power series for x < 1.
        For x >= 1 auxiliary functions f(x) and g(x) are employed
        such that

        C(x) = 0.5 + f(x) sin( pi/2 x**2 ) - g(x) cos( pi/2 x**2 )
        S(x) = 0.5 - f(x) cos( pi/2 x**2 ) - g(x) sin( pi/2 x**2 )



        ACCURACY:

         Relative error.

        Arithmetic  function   domain     # trials      peak         rms
          IEEE       S(x)      0, 10       10000       2.0e-15     3.2e-16
          IEEE       C(x)      0, 10       10000       1.8e-15     3.3e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static void fresnelintegral(double x,
            ref double c,
            ref double s,
            alglib.xparams _params)
        {
            double xxa = 0;
            double f = 0;
            double g = 0;
            double cc = 0;
            double ss = 0;
            double t = 0;
            double u = 0;
            double x2 = 0;
            double sn = 0;
            double sd = 0;
            double cn = 0;
            double cd = 0;
            double fn = 0;
            double fd = 0;
            double gn = 0;
            double gd = 0;
            double mpi = 0;
            double mpio2 = 0;

            mpi = 3.14159265358979323846;
            mpio2 = 1.57079632679489661923;
            xxa = x;
            x = Math.Abs(xxa);
            x2 = x*x;
            if( (double)(x2)<(double)(2.5625) )
            {
                t = x2*x2;
                sn = -2.99181919401019853726E3;
                sn = sn*t+7.08840045257738576863E5;
                sn = sn*t-6.29741486205862506537E7;
                sn = sn*t+2.54890880573376359104E9;
                sn = sn*t-4.42979518059697779103E10;
                sn = sn*t+3.18016297876567817986E11;
                sd = 1.00000000000000000000E0;
                sd = sd*t+2.81376268889994315696E2;
                sd = sd*t+4.55847810806532581675E4;
                sd = sd*t+5.17343888770096400730E6;
                sd = sd*t+4.19320245898111231129E8;
                sd = sd*t+2.24411795645340920940E10;
                sd = sd*t+6.07366389490084639049E11;
                cn = -4.98843114573573548651E-8;
                cn = cn*t+9.50428062829859605134E-6;
                cn = cn*t-6.45191435683965050962E-4;
                cn = cn*t+1.88843319396703850064E-2;
                cn = cn*t-2.05525900955013891793E-1;
                cn = cn*t+9.99999999999999998822E-1;
                cd = 3.99982968972495980367E-12;
                cd = cd*t+9.15439215774657478799E-10;
                cd = cd*t+1.25001862479598821474E-7;
                cd = cd*t+1.22262789024179030997E-5;
                cd = cd*t+8.68029542941784300606E-4;
                cd = cd*t+4.12142090722199792936E-2;
                cd = cd*t+1.00000000000000000118E0;
                s = Math.Sign(xxa)*x*x2*sn/sd;
                c = Math.Sign(xxa)*x*cn/cd;
                return;
            }
            if( (double)(x)>(double)(36974.0) )
            {
                c = Math.Sign(xxa)*0.5;
                s = Math.Sign(xxa)*0.5;
                return;
            }
            x2 = x*x;
            t = mpi*x2;
            u = 1/(t*t);
            t = 1/t;
            fn = 4.21543555043677546506E-1;
            fn = fn*u+1.43407919780758885261E-1;
            fn = fn*u+1.15220955073585758835E-2;
            fn = fn*u+3.45017939782574027900E-4;
            fn = fn*u+4.63613749287867322088E-6;
            fn = fn*u+3.05568983790257605827E-8;
            fn = fn*u+1.02304514164907233465E-10;
            fn = fn*u+1.72010743268161828879E-13;
            fn = fn*u+1.34283276233062758925E-16;
            fn = fn*u+3.76329711269987889006E-20;
            fd = 1.00000000000000000000E0;
            fd = fd*u+7.51586398353378947175E-1;
            fd = fd*u+1.16888925859191382142E-1;
            fd = fd*u+6.44051526508858611005E-3;
            fd = fd*u+1.55934409164153020873E-4;
            fd = fd*u+1.84627567348930545870E-6;
            fd = fd*u+1.12699224763999035261E-8;
            fd = fd*u+3.60140029589371370404E-11;
            fd = fd*u+5.88754533621578410010E-14;
            fd = fd*u+4.52001434074129701496E-17;
            fd = fd*u+1.25443237090011264384E-20;
            gn = 5.04442073643383265887E-1;
            gn = gn*u+1.97102833525523411709E-1;
            gn = gn*u+1.87648584092575249293E-2;
            gn = gn*u+6.84079380915393090172E-4;
            gn = gn*u+1.15138826111884280931E-5;
            gn = gn*u+9.82852443688422223854E-8;
            gn = gn*u+4.45344415861750144738E-10;
            gn = gn*u+1.08268041139020870318E-12;
            gn = gn*u+1.37555460633261799868E-15;
            gn = gn*u+8.36354435630677421531E-19;
            gn = gn*u+1.86958710162783235106E-22;
            gd = 1.00000000000000000000E0;
            gd = gd*u+1.47495759925128324529E0;
            gd = gd*u+3.37748989120019970451E-1;
            gd = gd*u+2.53603741420338795122E-2;
            gd = gd*u+8.14679107184306179049E-4;
            gd = gd*u+1.27545075667729118702E-5;
            gd = gd*u+1.04314589657571990585E-7;
            gd = gd*u+4.60680728146520428211E-10;
            gd = gd*u+1.10273215066240270757E-12;
            gd = gd*u+1.38796531259578871258E-15;
            gd = gd*u+8.39158816283118707363E-19;
            gd = gd*u+1.86958710162783236342E-22;
            f = 1-u*fn/fd;
            g = t*gn/gd;
            t = mpio2*x2;
            cc = Math.Cos(t);
            ss = Math.Sin(t);
            t = mpi*x;
            c = 0.5+(f*ss-g*cc)/t;
            s = 0.5-(f*cc+g*ss)/t;
            c = c*Math.Sign(xxa);
            s = s*Math.Sign(xxa);
        }


    }
    public class psif
    {
        /*************************************************************************
        Psi (digamma) function

                     d      -
          psi(x)  =  -- ln | (x)
                     dx

        is the logarithmic derivative of the gamma function.
        For integer x,
                          n-1
                           -
        psi(n) = -EUL  +   >  1/k.
                           -
                          k=1

        This formula is used for 0 < n <= 10.  If x is negative, it
        is transformed to a positive argument by the reflection
        formula  psi(1-x) = psi(x) + pi cot(pi x).
        For general positive x, the argument is made greater than 10
        using the recurrence  psi(x+1) = psi(x) + 1/x.
        Then the following asymptotic expansion is applied:

                                  inf.   B
                                   -      2k
        psi(x) = log(x) - 1/2x -   >   -------
                                   -        2k
                                  k=1   2k x

        where the B2k are Bernoulli numbers.

        ACCURACY:
           Relative error (except absolute when |psi| < 1):
        arithmetic   domain     # trials      peak         rms
           IEEE      0,30        30000       1.3e-15     1.4e-16
           IEEE      -30,0       40000       1.5e-15     2.2e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1992, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double psi(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double p = 0;
            double q = 0;
            double nz = 0;
            double s = 0;
            double w = 0;
            double y = 0;
            double z = 0;
            double polv = 0;
            int i = 0;
            int n = 0;
            int negative = 0;

            negative = 0;
            nz = 0.0;
            if( (double)(x)<=(double)(0) )
            {
                negative = 1;
                q = x;
                p = (int)Math.Floor(q);
                if( (double)(p)==(double)(q) )
                {
                    alglib.ap.assert(false, "Singularity in Psi(x)");
                    result = math.maxrealnumber;
                    return result;
                }
                nz = q-p;
                if( (double)(nz)!=(double)(0.5) )
                {
                    if( (double)(nz)>(double)(0.5) )
                    {
                        p = p+1.0;
                        nz = q-p;
                    }
                    nz = Math.PI/Math.Tan(Math.PI*nz);
                }
                else
                {
                    nz = 0.0;
                }
                x = 1.0-x;
            }
            if( (double)(x)<=(double)(10.0) && (double)(x)==(double)((int)Math.Floor(x)) )
            {
                y = 0.0;
                n = (int)Math.Floor(x);
                for(i=1; i<=n-1; i++)
                {
                    w = i;
                    y = y+1.0/w;
                }
                y = y-0.57721566490153286061;
            }
            else
            {
                s = x;
                w = 0.0;
                while( (double)(s)<(double)(10.0) )
                {
                    w = w+1.0/s;
                    s = s+1.0;
                }
                if( (double)(s)<(double)(1.0E17) )
                {
                    z = 1.0/(s*s);
                    polv = 8.33333333333333333333E-2;
                    polv = polv*z-2.10927960927960927961E-2;
                    polv = polv*z+7.57575757575757575758E-3;
                    polv = polv*z-4.16666666666666666667E-3;
                    polv = polv*z+3.96825396825396825397E-3;
                    polv = polv*z-8.33333333333333333333E-3;
                    polv = polv*z+8.33333333333333333333E-2;
                    y = z*polv;
                }
                else
                {
                    y = 0.0;
                }
                y = Math.Log(s)-0.5/s-y-w;
            }
            if( negative!=0 )
            {
                y = y-nz;
            }
            result = y;
            return result;
        }


    }
    public class airyf
    {
        /*************************************************************************
        Airy function

        Solution of the differential equation

        y"(x) = xy.

        The function returns the two independent solutions Ai, Bi
        and their first derivatives Ai'(x), Bi'(x).

        Evaluation is by power series summation for small x,
        by rational minimax approximations for large x.



        ACCURACY:
        Error criterion is absolute when function <= 1, relative
        when function > 1, except * denotes relative error criterion.
        For large negative x, the absolute error increases as x^1.5.
        For large positive x, the relative error increases as x^1.5.

        Arithmetic  domain   function  # trials      peak         rms
        IEEE        -10, 0     Ai        10000       1.6e-15     2.7e-16
        IEEE          0, 10    Ai        10000       2.3e-14*    1.8e-15*
        IEEE        -10, 0     Ai'       10000       4.6e-15     7.6e-16
        IEEE          0, 10    Ai'       10000       1.8e-14*    1.5e-15*
        IEEE        -10, 10    Bi        30000       4.2e-15     5.3e-16
        IEEE        -10, 10    Bi'       30000       4.9e-15     7.3e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static void airy(double x,
            ref double ai,
            ref double aip,
            ref double bi,
            ref double bip,
            alglib.xparams _params)
        {
            double z = 0;
            double zz = 0;
            double t = 0;
            double f = 0;
            double g = 0;
            double uf = 0;
            double ug = 0;
            double k = 0;
            double zeta = 0;
            double theta = 0;
            int domflg = 0;
            double c1 = 0;
            double c2 = 0;
            double sqrt3 = 0;
            double sqpii = 0;
            double afn = 0;
            double afd = 0;
            double agn = 0;
            double agd = 0;
            double apfn = 0;
            double apfd = 0;
            double apgn = 0;
            double apgd = 0;
            double an = 0;
            double ad = 0;
            double apn = 0;
            double apd = 0;
            double bn16 = 0;
            double bd16 = 0;
            double bppn = 0;
            double bppd = 0;

            ai = 0;
            aip = 0;
            bi = 0;
            bip = 0;

            sqpii = 5.64189583547756286948E-1;
            c1 = 0.35502805388781723926;
            c2 = 0.258819403792806798405;
            sqrt3 = 1.732050807568877293527;
            domflg = 0;
            if( (double)(x)>(double)(25.77) )
            {
                ai = 0;
                aip = 0;
                bi = math.maxrealnumber;
                bip = math.maxrealnumber;
                return;
            }
            if( (double)(x)<(double)(-2.09) )
            {
                domflg = 15;
                t = Math.Sqrt(-x);
                zeta = -(2.0*x*t/3.0);
                t = Math.Sqrt(t);
                k = sqpii/t;
                z = 1.0/zeta;
                zz = z*z;
                afn = -1.31696323418331795333E-1;
                afn = afn*zz-6.26456544431912369773E-1;
                afn = afn*zz-6.93158036036933542233E-1;
                afn = afn*zz-2.79779981545119124951E-1;
                afn = afn*zz-4.91900132609500318020E-2;
                afn = afn*zz-4.06265923594885404393E-3;
                afn = afn*zz-1.59276496239262096340E-4;
                afn = afn*zz-2.77649108155232920844E-6;
                afn = afn*zz-1.67787698489114633780E-8;
                afd = 1.00000000000000000000E0;
                afd = afd*zz+1.33560420706553243746E1;
                afd = afd*zz+3.26825032795224613948E1;
                afd = afd*zz+2.67367040941499554804E1;
                afd = afd*zz+9.18707402907259625840E0;
                afd = afd*zz+1.47529146771666414581E0;
                afd = afd*zz+1.15687173795188044134E-1;
                afd = afd*zz+4.40291641615211203805E-3;
                afd = afd*zz+7.54720348287414296618E-5;
                afd = afd*zz+4.51850092970580378464E-7;
                uf = 1.0+zz*afn/afd;
                agn = 1.97339932091685679179E-2;
                agn = agn*zz+3.91103029615688277255E-1;
                agn = agn*zz+1.06579897599595591108E0;
                agn = agn*zz+9.39169229816650230044E-1;
                agn = agn*zz+3.51465656105547619242E-1;
                agn = agn*zz+6.33888919628925490927E-2;
                agn = agn*zz+5.85804113048388458567E-3;
                agn = agn*zz+2.82851600836737019778E-4;
                agn = agn*zz+6.98793669997260967291E-6;
                agn = agn*zz+8.11789239554389293311E-8;
                agn = agn*zz+3.41551784765923618484E-10;
                agd = 1.00000000000000000000E0;
                agd = agd*zz+9.30892908077441974853E0;
                agd = agd*zz+1.98352928718312140417E1;
                agd = agd*zz+1.55646628932864612953E1;
                agd = agd*zz+5.47686069422975497931E0;
                agd = agd*zz+9.54293611618961883998E-1;
                agd = agd*zz+8.64580826352392193095E-2;
                agd = agd*zz+4.12656523824222607191E-3;
                agd = agd*zz+1.01259085116509135510E-4;
                agd = agd*zz+1.17166733214413521882E-6;
                agd = agd*zz+4.91834570062930015649E-9;
                ug = z*agn/agd;
                theta = zeta+0.25*Math.PI;
                f = Math.Sin(theta);
                g = Math.Cos(theta);
                ai = k*(f*uf-g*ug);
                bi = k*(g*uf+f*ug);
                apfn = 1.85365624022535566142E-1;
                apfn = apfn*zz+8.86712188052584095637E-1;
                apfn = apfn*zz+9.87391981747398547272E-1;
                apfn = apfn*zz+4.01241082318003734092E-1;
                apfn = apfn*zz+7.10304926289631174579E-2;
                apfn = apfn*zz+5.90618657995661810071E-3;
                apfn = apfn*zz+2.33051409401776799569E-4;
                apfn = apfn*zz+4.08718778289035454598E-6;
                apfn = apfn*zz+2.48379932900442457853E-8;
                apfd = 1.00000000000000000000E0;
                apfd = apfd*zz+1.47345854687502542552E1;
                apfd = apfd*zz+3.75423933435489594466E1;
                apfd = apfd*zz+3.14657751203046424330E1;
                apfd = apfd*zz+1.09969125207298778536E1;
                apfd = apfd*zz+1.78885054766999417817E0;
                apfd = apfd*zz+1.41733275753662636873E-1;
                apfd = apfd*zz+5.44066067017226003627E-3;
                apfd = apfd*zz+9.39421290654511171663E-5;
                apfd = apfd*zz+5.65978713036027009243E-7;
                uf = 1.0+zz*apfn/apfd;
                apgn = -3.55615429033082288335E-2;
                apgn = apgn*zz-6.37311518129435504426E-1;
                apgn = apgn*zz-1.70856738884312371053E0;
                apgn = apgn*zz-1.50221872117316635393E0;
                apgn = apgn*zz-5.63606665822102676611E-1;
                apgn = apgn*zz-1.02101031120216891789E-1;
                apgn = apgn*zz-9.48396695961445269093E-3;
                apgn = apgn*zz-4.60325307486780994357E-4;
                apgn = apgn*zz-1.14300836484517375919E-5;
                apgn = apgn*zz-1.33415518685547420648E-7;
                apgn = apgn*zz-5.63803833958893494476E-10;
                apgd = 1.00000000000000000000E0;
                apgd = apgd*zz+9.85865801696130355144E0;
                apgd = apgd*zz+2.16401867356585941885E1;
                apgd = apgd*zz+1.73130776389749389525E1;
                apgd = apgd*zz+6.17872175280828766327E0;
                apgd = apgd*zz+1.08848694396321495475E0;
                apgd = apgd*zz+9.95005543440888479402E-2;
                apgd = apgd*zz+4.78468199683886610842E-3;
                apgd = apgd*zz+1.18159633322838625562E-4;
                apgd = apgd*zz+1.37480673554219441465E-6;
                apgd = apgd*zz+5.79912514929147598821E-9;
                ug = z*apgn/apgd;
                k = sqpii*t;
                aip = -(k*(g*uf+f*ug));
                bip = k*(f*uf-g*ug);
                return;
            }
            if( (double)(x)>=(double)(2.09) )
            {
                domflg = 5;
                t = Math.Sqrt(x);
                zeta = 2.0*x*t/3.0;
                g = Math.Exp(zeta);
                t = Math.Sqrt(t);
                k = 2.0*t*g;
                z = 1.0/zeta;
                an = 3.46538101525629032477E-1;
                an = an*z+1.20075952739645805542E1;
                an = an*z+7.62796053615234516538E1;
                an = an*z+1.68089224934630576269E2;
                an = an*z+1.59756391350164413639E2;
                an = an*z+7.05360906840444183113E1;
                an = an*z+1.40264691163389668864E1;
                an = an*z+9.99999999999999995305E-1;
                ad = 5.67594532638770212846E-1;
                ad = ad*z+1.47562562584847203173E1;
                ad = ad*z+8.45138970141474626562E1;
                ad = ad*z+1.77318088145400459522E2;
                ad = ad*z+1.64234692871529701831E2;
                ad = ad*z+7.14778400825575695274E1;
                ad = ad*z+1.40959135607834029598E1;
                ad = ad*z+1.00000000000000000470E0;
                f = an/ad;
                ai = sqpii*f/k;
                k = -(0.5*sqpii*t/g);
                apn = 6.13759184814035759225E-1;
                apn = apn*z+1.47454670787755323881E1;
                apn = apn*z+8.20584123476060982430E1;
                apn = apn*z+1.71184781360976385540E2;
                apn = apn*z+1.59317847137141783523E2;
                apn = apn*z+6.99778599330103016170E1;
                apn = apn*z+1.39470856980481566958E1;
                apn = apn*z+1.00000000000000000550E0;
                apd = 3.34203677749736953049E-1;
                apd = apd*z+1.11810297306158156705E1;
                apd = apd*z+7.11727352147859965283E1;
                apd = apd*z+1.58778084372838313640E2;
                apd = apd*z+1.53206427475809220834E2;
                apd = apd*z+6.86752304592780337944E1;
                apd = apd*z+1.38498634758259442477E1;
                apd = apd*z+9.99999999999999994502E-1;
                f = apn/apd;
                aip = f*k;
                if( (double)(x)>(double)(8.3203353) )
                {
                    bn16 = -2.53240795869364152689E-1;
                    bn16 = bn16*z+5.75285167332467384228E-1;
                    bn16 = bn16*z-3.29907036873225371650E-1;
                    bn16 = bn16*z+6.44404068948199951727E-2;
                    bn16 = bn16*z-3.82519546641336734394E-3;
                    bd16 = 1.00000000000000000000E0;
                    bd16 = bd16*z-7.15685095054035237902E0;
                    bd16 = bd16*z+1.06039580715664694291E1;
                    bd16 = bd16*z-5.23246636471251500874E0;
                    bd16 = bd16*z+9.57395864378383833152E-1;
                    bd16 = bd16*z-5.50828147163549611107E-2;
                    f = z*bn16/bd16;
                    k = sqpii*g;
                    bi = k*(1.0+f)/t;
                    bppn = 4.65461162774651610328E-1;
                    bppn = bppn*z-1.08992173800493920734E0;
                    bppn = bppn*z+6.38800117371827987759E-1;
                    bppn = bppn*z-1.26844349553102907034E-1;
                    bppn = bppn*z+7.62487844342109852105E-3;
                    bppd = 1.00000000000000000000E0;
                    bppd = bppd*z-8.70622787633159124240E0;
                    bppd = bppd*z+1.38993162704553213172E1;
                    bppd = bppd*z-7.14116144616431159572E0;
                    bppd = bppd*z+1.34008595960680518666E0;
                    bppd = bppd*z-7.84273211323341930448E-2;
                    f = z*bppn/bppd;
                    bip = k*t*(1.0+f);
                    return;
                }
            }
            f = 1.0;
            g = x;
            t = 1.0;
            uf = 1.0;
            ug = x;
            k = 1.0;
            z = x*x*x;
            while( (double)(t)>(double)(math.machineepsilon) )
            {
                uf = uf*z;
                k = k+1.0;
                uf = uf/k;
                ug = ug*z;
                k = k+1.0;
                ug = ug/k;
                uf = uf/k;
                f = f+uf;
                k = k+1.0;
                ug = ug/k;
                g = g+ug;
                t = Math.Abs(uf/f);
            }
            uf = c1*f;
            ug = c2*g;
            if( domflg%2==0 )
            {
                ai = uf-ug;
            }
            if( domflg/2%2==0 )
            {
                bi = sqrt3*(uf+ug);
            }
            k = 4.0;
            uf = x*x/2.0;
            ug = z/3.0;
            f = uf;
            g = 1.0+ug;
            uf = uf/3.0;
            t = 1.0;
            while( (double)(t)>(double)(math.machineepsilon) )
            {
                uf = uf*z;
                ug = ug/k;
                k = k+1.0;
                ug = ug*z;
                uf = uf/k;
                f = f+uf;
                k = k+1.0;
                ug = ug/k;
                uf = uf/k;
                g = g+ug;
                k = k+1.0;
                t = Math.Abs(ug/g);
            }
            uf = c1*f;
            ug = c2*g;
            if( domflg/4%2==0 )
            {
                aip = uf-ug;
            }
            if( domflg/8%2==0 )
            {
                bip = sqrt3*(uf+ug);
            }
        }


    }
    public class dawson
    {
        /*************************************************************************
        Dawson's Integral

        Approximates the integral

                                    x
                                    -
                             2     | |        2
         dawsn(x)  =  exp( -x  )   |    exp( t  ) dt
                                 | |
                                  -
                                  0

        Three different rational approximations are employed, for
        the intervals 0 to 3.25; 3.25 to 6.25; and 6.25 up.

        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE      0,10        10000       6.9e-16     1.0e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double dawsonintegral(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double x2 = 0;
            double y = 0;
            int sg = 0;
            double an = 0;
            double ad = 0;
            double bn = 0;
            double bd = 0;
            double cn = 0;
            double cd = 0;

            sg = 1;
            if( (double)(x)<(double)(0) )
            {
                sg = -1;
                x = -x;
            }
            if( (double)(x)<(double)(3.25) )
            {
                x2 = x*x;
                an = 1.13681498971755972054E-11;
                an = an*x2+8.49262267667473811108E-10;
                an = an*x2+1.94434204175553054283E-8;
                an = an*x2+9.53151741254484363489E-7;
                an = an*x2+3.07828309874913200438E-6;
                an = an*x2+3.52513368520288738649E-4;
                an = an*x2+-8.50149846724410912031E-4;
                an = an*x2+4.22618223005546594270E-2;
                an = an*x2+-9.17480371773452345351E-2;
                an = an*x2+9.99999999999999994612E-1;
                ad = 2.40372073066762605484E-11;
                ad = ad*x2+1.48864681368493396752E-9;
                ad = ad*x2+5.21265281010541664570E-8;
                ad = ad*x2+1.27258478273186970203E-6;
                ad = ad*x2+2.32490249820789513991E-5;
                ad = ad*x2+3.25524741826057911661E-4;
                ad = ad*x2+3.48805814657162590916E-3;
                ad = ad*x2+2.79448531198828973716E-2;
                ad = ad*x2+1.58874241960120565368E-1;
                ad = ad*x2+5.74918629489320327824E-1;
                ad = ad*x2+1.00000000000000000539E0;
                y = x*an/ad;
                result = sg*y;
                return result;
            }
            x2 = 1.0/(x*x);
            if( (double)(x)<(double)(6.25) )
            {
                bn = 5.08955156417900903354E-1;
                bn = bn*x2-2.44754418142697847934E-1;
                bn = bn*x2+9.41512335303534411857E-2;
                bn = bn*x2-2.18711255142039025206E-2;
                bn = bn*x2+3.66207612329569181322E-3;
                bn = bn*x2-4.23209114460388756528E-4;
                bn = bn*x2+3.59641304793896631888E-5;
                bn = bn*x2-2.14640351719968974225E-6;
                bn = bn*x2+9.10010780076391431042E-8;
                bn = bn*x2-2.40274520828250956942E-9;
                bn = bn*x2+3.59233385440928410398E-11;
                bd = 1.00000000000000000000E0;
                bd = bd*x2-6.31839869873368190192E-1;
                bd = bd*x2+2.36706788228248691528E-1;
                bd = bd*x2-5.31806367003223277662E-2;
                bd = bd*x2+8.48041718586295374409E-3;
                bd = bd*x2-9.47996768486665330168E-4;
                bd = bd*x2+7.81025592944552338085E-5;
                bd = bd*x2-4.55875153252442634831E-6;
                bd = bd*x2+1.89100358111421846170E-7;
                bd = bd*x2-4.91324691331920606875E-9;
                bd = bd*x2+7.18466403235734541950E-11;
                y = 1.0/x+x2*bn/(bd*x);
                result = sg*0.5*y;
                return result;
            }
            if( (double)(x)>(double)(1.0E9) )
            {
                result = sg*0.5/x;
                return result;
            }
            cn = -5.90592860534773254987E-1;
            cn = cn*x2+6.29235242724368800674E-1;
            cn = cn*x2-1.72858975380388136411E-1;
            cn = cn*x2+1.64837047825189632310E-2;
            cn = cn*x2-4.86827613020462700845E-4;
            cd = 1.00000000000000000000E0;
            cd = cd*x2-2.69820057197544900361E0;
            cd = cd*x2+1.73270799045947845857E0;
            cd = cd*x2-3.93708582281939493482E-1;
            cd = cd*x2+3.44278924041233391079E-2;
            cd = cd*x2-9.73655226040941223894E-4;
            y = 1.0/x+x2*cn/(cd*x);
            result = sg*0.5*y;
            return result;
        }


    }
    public class hermite
    {
        /*************************************************************************
        Calculation of the value of the Hermite polynomial.

        Parameters:
            n   -   degree, n>=0
            x   -   argument

        Result:
            the value of the Hermite polynomial Hn at x
        *************************************************************************/
        public static double hermitecalculate(int n,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            int i = 0;
            double a = 0;
            double b = 0;

            result = 0;
            
            //
            // Prepare A and B
            //
            a = 1;
            b = 2*x;
            
            //
            // Special cases: N=0 or N=1
            //
            if( n==0 )
            {
                result = a;
                return result;
            }
            if( n==1 )
            {
                result = b;
                return result;
            }
            
            //
            // General case: N>=2
            //
            for(i=2; i<=n; i++)
            {
                result = 2*x*b-2*(i-1)*a;
                a = b;
                b = result;
            }
            return result;
        }


        /*************************************************************************
        Summation of Hermite polynomials using Clenshaw's recurrence formula.

        This routine calculates
            c[0]*H0(x) + c[1]*H1(x) + ... + c[N]*HN(x)

        Parameters:
            n   -   degree, n>=0
            x   -   argument

        Result:
            the value of the Hermite polynomial at x
        *************************************************************************/
        public static double hermitesum(double[] c,
            int n,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double b1 = 0;
            double b2 = 0;
            int i = 0;

            b1 = 0;
            b2 = 0;
            result = 0;
            for(i=n; i>=0; i--)
            {
                result = 2*(x*b1-(i+1)*b2)+c[i];
                b2 = b1;
                b1 = result;
            }
            return result;
        }


        /*************************************************************************
        Representation of Hn as C[0] + C[1]*X + ... + C[N]*X^N

        Input parameters:
            N   -   polynomial degree, n>=0

        Output parameters:
            C   -   coefficients
        *************************************************************************/
        public static void hermitecoefficients(int n,
            ref double[] c,
            alglib.xparams _params)
        {
            int i = 0;

            c = new double[0];

            c = new double[n+1];
            for(i=0; i<=n; i++)
            {
                c[i] = 0;
            }
            c[n] = Math.Exp(n*Math.Log(2));
            for(i=0; i<=n/2-1; i++)
            {
                c[n-2*(i+1)] = -(c[n-2*i]*(n-2*i)*(n-2*i-1)/4/(i+1));
            }
        }


    }
    public class legendre
    {
        /*************************************************************************
        Calculation of the value of the Legendre polynomial Pn.

        Parameters:
            n   -   degree, n>=0
            x   -   argument

        Result:
            the value of the Legendre polynomial Pn at x
        *************************************************************************/
        public static double legendrecalculate(int n,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double a = 0;
            double b = 0;
            int i = 0;

            result = 1;
            a = 1;
            b = x;
            if( n==0 )
            {
                result = a;
                return result;
            }
            if( n==1 )
            {
                result = b;
                return result;
            }
            for(i=2; i<=n; i++)
            {
                result = ((2*i-1)*x*b-(i-1)*a)/i;
                a = b;
                b = result;
            }
            return result;
        }


        /*************************************************************************
        Summation of Legendre polynomials using Clenshaw's recurrence formula.

        This routine calculates
            c[0]*P0(x) + c[1]*P1(x) + ... + c[N]*PN(x)

        Parameters:
            n   -   degree, n>=0
            x   -   argument

        Result:
            the value of the Legendre polynomial at x
        *************************************************************************/
        public static double legendresum(double[] c,
            int n,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double b1 = 0;
            double b2 = 0;
            int i = 0;

            b1 = 0;
            b2 = 0;
            result = 0;
            for(i=n; i>=0; i--)
            {
                result = (2*i+1)*x*b1/(i+1)-(i+1)*b2/(i+2)+c[i];
                b2 = b1;
                b1 = result;
            }
            return result;
        }


        /*************************************************************************
        Representation of Pn as C[0] + C[1]*X + ... + C[N]*X^N

        Input parameters:
            N   -   polynomial degree, n>=0

        Output parameters:
            C   -   coefficients
        *************************************************************************/
        public static void legendrecoefficients(int n,
            ref double[] c,
            alglib.xparams _params)
        {
            int i = 0;

            c = new double[0];

            c = new double[n+1];
            for(i=0; i<=n; i++)
            {
                c[i] = 0;
            }
            c[n] = 1;
            for(i=1; i<=n; i++)
            {
                c[n] = c[n]*(n+i)/2/i;
            }
            for(i=0; i<=n/2-1; i++)
            {
                c[n-2*(i+1)] = -(c[n-2*i]*(n-2*i)*(n-2*i-1)/2/(i+1)/(2*(n-i)-1));
            }
        }


    }
    public class bessel
    {
        /*************************************************************************
        Bessel function of order zero

        Returns Bessel function of order zero of the argument.

        The domain is divided into the intervals [0, 5] and
        (5, infinity). In the first interval the following rational
        approximation is used:


               2         2
        (w - r  ) (w - r  ) P (w) / Q (w)
              1         2    3       8

                   2
        where w = x  and the two r's are zeros of the function.

        In the second interval, the Hankel asymptotic expansion
        is employed with two rational functions of degree 6/6
        and 7/7.

        ACCURACY:

                             Absolute error:
        arithmetic   domain     # trials      peak         rms
           IEEE      0, 30       60000       4.2e-16     1.1e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double besselj0(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double xsq = 0;
            double nn = 0;
            double pzero = 0;
            double qzero = 0;
            double p1 = 0;
            double q1 = 0;

            if( (double)(x)<(double)(0) )
            {
                x = -x;
            }
            if( (double)(x)>(double)(8.0) )
            {
                besselasympt0(x, ref pzero, ref qzero, _params);
                nn = x-Math.PI/4;
                result = Math.Sqrt(2/Math.PI/x)*(pzero*Math.Cos(nn)-qzero*Math.Sin(nn));
                return result;
            }
            xsq = math.sqr(x);
            p1 = 26857.86856980014981415848441;
            p1 = -40504123.71833132706360663322+xsq*p1;
            p1 = 25071582855.36881945555156435+xsq*p1;
            p1 = -8085222034853.793871199468171+xsq*p1;
            p1 = 1434354939140344.111664316553+xsq*p1;
            p1 = -136762035308817138.6865416609+xsq*p1;
            p1 = 6382059341072356562.289432465+xsq*p1;
            p1 = -117915762910761053603.8440800+xsq*p1;
            p1 = 493378725179413356181.6813446+xsq*p1;
            q1 = 1.0;
            q1 = 1363.063652328970604442810507+xsq*q1;
            q1 = 1114636.098462985378182402543+xsq*q1;
            q1 = 669998767.2982239671814028660+xsq*q1;
            q1 = 312304311494.1213172572469442+xsq*q1;
            q1 = 112775673967979.8507056031594+xsq*q1;
            q1 = 30246356167094626.98627330784+xsq*q1;
            q1 = 5428918384092285160.200195092+xsq*q1;
            q1 = 493378725179413356211.3278438+xsq*q1;
            result = p1/q1;
            return result;
        }


        /*************************************************************************
        Bessel function of order one

        Returns Bessel function of order one of the argument.

        The domain is divided into the intervals [0, 8] and
        (8, infinity). In the first interval a 24 term Chebyshev
        expansion is used. In the second, the asymptotic
        trigonometric representation is employed using two
        rational functions of degree 5/5.

        ACCURACY:

                             Absolute error:
        arithmetic   domain      # trials      peak         rms
           IEEE      0, 30       30000       2.6e-16     1.1e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double besselj1(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double s = 0;
            double xsq = 0;
            double nn = 0;
            double pzero = 0;
            double qzero = 0;
            double p1 = 0;
            double q1 = 0;

            s = Math.Sign(x);
            if( (double)(x)<(double)(0) )
            {
                x = -x;
            }
            if( (double)(x)>(double)(8.0) )
            {
                besselasympt1(x, ref pzero, ref qzero, _params);
                nn = x-3*Math.PI/4;
                result = Math.Sqrt(2/Math.PI/x)*(pzero*Math.Cos(nn)-qzero*Math.Sin(nn));
                if( (double)(s)<(double)(0) )
                {
                    result = -result;
                }
                return result;
            }
            xsq = math.sqr(x);
            p1 = 2701.122710892323414856790990;
            p1 = -4695753.530642995859767162166+xsq*p1;
            p1 = 3413234182.301700539091292655+xsq*p1;
            p1 = -1322983480332.126453125473247+xsq*p1;
            p1 = 290879526383477.5409737601689+xsq*p1;
            p1 = -35888175699101060.50743641413+xsq*p1;
            p1 = 2316433580634002297.931815435+xsq*p1;
            p1 = -66721065689249162980.20941484+xsq*p1;
            p1 = 581199354001606143928.050809+xsq*p1;
            q1 = 1.0;
            q1 = 1606.931573481487801970916749+xsq*q1;
            q1 = 1501793.594998585505921097578+xsq*q1;
            q1 = 1013863514.358673989967045588+xsq*q1;
            q1 = 524371026216.7649715406728642+xsq*q1;
            q1 = 208166122130760.7351240184229+xsq*q1;
            q1 = 60920613989175217.46105196863+xsq*q1;
            q1 = 11857707121903209998.37113348+xsq*q1;
            q1 = 1162398708003212287858.529400+xsq*q1;
            result = s*x*p1/q1;
            return result;
        }


        /*************************************************************************
        Bessel function of integer order

        Returns Bessel function of order n, where n is a
        (possibly negative) integer.

        The ratio of jn(x) to j0(x) is computed by backward
        recurrence.  First the ratio jn/jn-1 is found by a
        continued fraction expansion.  Then the recurrence
        relating successive orders is applied until j0 or j1 is
        reached.

        If n = 0 or 1 the routine for j0 or j1 is called
        directly.

        ACCURACY:

                             Absolute error:
        arithmetic   range      # trials      peak         rms
           IEEE      0, 30        5000       4.4e-16     7.9e-17


        Not suitable for large n or x. Use jv() (fractional order) instead.

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double besseljn(int n,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double pkm2 = 0;
            double pkm1 = 0;
            double pk = 0;
            double xk = 0;
            double r = 0;
            double ans = 0;
            int k = 0;
            int sg = 0;

            if( n<0 )
            {
                n = -n;
                if( n%2==0 )
                {
                    sg = 1;
                }
                else
                {
                    sg = -1;
                }
            }
            else
            {
                sg = 1;
            }
            if( (double)(x)<(double)(0) )
            {
                if( n%2!=0 )
                {
                    sg = -sg;
                }
                x = -x;
            }
            if( n==0 )
            {
                result = sg*besselj0(x, _params);
                return result;
            }
            if( n==1 )
            {
                result = sg*besselj1(x, _params);
                return result;
            }
            if( n==2 )
            {
                if( (double)(x)==(double)(0) )
                {
                    result = 0;
                }
                else
                {
                    result = sg*(2.0*besselj1(x, _params)/x-besselj0(x, _params));
                }
                return result;
            }
            if( (double)(x)<(double)(math.machineepsilon) )
            {
                result = 0;
                return result;
            }
            k = 53;
            pk = 2*(n+k);
            ans = pk;
            xk = x*x;
            do
            {
                pk = pk-2.0;
                ans = pk-xk/ans;
                k = k-1;
            }
            while( k!=0 );
            ans = x/ans;
            pk = 1.0;
            pkm1 = 1.0/ans;
            k = n-1;
            r = 2*k;
            do
            {
                pkm2 = (pkm1*r-pk*x)/x;
                pk = pkm1;
                pkm1 = pkm2;
                r = r-2.0;
                k = k-1;
            }
            while( k!=0 );
            if( (double)(Math.Abs(pk))>(double)(Math.Abs(pkm1)) )
            {
                ans = besselj1(x, _params)/pk;
            }
            else
            {
                ans = besselj0(x, _params)/pkm1;
            }
            result = sg*ans;
            return result;
        }


        /*************************************************************************
        Bessel function of the second kind, order zero

        Returns Bessel function of the second kind, of order
        zero, of the argument.

        The domain is divided into the intervals [0, 5] and
        (5, infinity). In the first interval a rational approximation
        R(x) is employed to compute
          y0(x)  = R(x)  +   2 * log(x) * j0(x) / PI.
        Thus a call to j0() is required.

        In the second interval, the Hankel asymptotic expansion
        is employed with two rational functions of degree 6/6
        and 7/7.



        ACCURACY:

         Absolute error, when y0(x) < 1; else relative error:

        arithmetic   domain     # trials      peak         rms
           IEEE      0, 30       30000       1.3e-15     1.6e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double bessely0(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double nn = 0;
            double xsq = 0;
            double pzero = 0;
            double qzero = 0;
            double p4 = 0;
            double q4 = 0;

            if( (double)(x)>(double)(8.0) )
            {
                besselasympt0(x, ref pzero, ref qzero, _params);
                nn = x-Math.PI/4;
                result = Math.Sqrt(2/Math.PI/x)*(pzero*Math.Sin(nn)+qzero*Math.Cos(nn));
                return result;
            }
            xsq = math.sqr(x);
            p4 = -41370.35497933148554125235152;
            p4 = 59152134.65686889654273830069+xsq*p4;
            p4 = -34363712229.79040378171030138+xsq*p4;
            p4 = 10255208596863.94284509167421+xsq*p4;
            p4 = -1648605817185729.473122082537+xsq*p4;
            p4 = 137562431639934407.8571335453+xsq*p4;
            p4 = -5247065581112764941.297350814+xsq*p4;
            p4 = 65874732757195549259.99402049+xsq*p4;
            p4 = -27502866786291095837.01933175+xsq*p4;
            q4 = 1.0;
            q4 = 1282.452772478993804176329391+xsq*q4;
            q4 = 1001702.641288906265666651753+xsq*q4;
            q4 = 579512264.0700729537480087915+xsq*q4;
            q4 = 261306575504.1081249568482092+xsq*q4;
            q4 = 91620380340751.85262489147968+xsq*q4;
            q4 = 23928830434997818.57439356652+xsq*q4;
            q4 = 4192417043410839973.904769661+xsq*q4;
            q4 = 372645883898616588198.9980+xsq*q4;
            result = p4/q4+2/Math.PI*besselj0(x, _params)*Math.Log(x);
            return result;
        }


        /*************************************************************************
        Bessel function of second kind of order one

        Returns Bessel function of the second kind of order one
        of the argument.

        The domain is divided into the intervals [0, 8] and
        (8, infinity). In the first interval a 25 term Chebyshev
        expansion is used, and a call to j1() is required.
        In the second, the asymptotic trigonometric representation
        is employed using two rational functions of degree 5/5.

        ACCURACY:

                             Absolute error:
        arithmetic   domain      # trials      peak         rms
           IEEE      0, 30       30000       1.0e-15     1.3e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double bessely1(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double nn = 0;
            double xsq = 0;
            double pzero = 0;
            double qzero = 0;
            double p4 = 0;
            double q4 = 0;

            if( (double)(x)>(double)(8.0) )
            {
                besselasympt1(x, ref pzero, ref qzero, _params);
                nn = x-3*Math.PI/4;
                result = Math.Sqrt(2/Math.PI/x)*(pzero*Math.Sin(nn)+qzero*Math.Cos(nn));
                return result;
            }
            xsq = math.sqr(x);
            p4 = -2108847.540133123652824139923;
            p4 = 3639488548.124002058278999428+xsq*p4;
            p4 = -2580681702194.450950541426399+xsq*p4;
            p4 = 956993023992168.3481121552788+xsq*p4;
            p4 = -196588746272214065.8820322248+xsq*p4;
            p4 = 21931073399177975921.11427556+xsq*p4;
            p4 = -1212297555414509577913.561535+xsq*p4;
            p4 = 26554738314348543268942.48968+xsq*p4;
            p4 = -99637534243069222259967.44354+xsq*p4;
            q4 = 1.0;
            q4 = 1612.361029677000859332072312+xsq*q4;
            q4 = 1563282.754899580604737366452+xsq*q4;
            q4 = 1128686837.169442121732366891+xsq*q4;
            q4 = 646534088126.5275571961681500+xsq*q4;
            q4 = 297663212564727.6729292742282+xsq*q4;
            q4 = 108225825940881955.2553850180+xsq*q4;
            q4 = 29549879358971486742.90758119+xsq*q4;
            q4 = 5435310377188854170800.653097+xsq*q4;
            q4 = 508206736694124324531442.4152+xsq*q4;
            result = x*p4/q4+2/Math.PI*(besselj1(x, _params)*Math.Log(x)-1/x);
            return result;
        }


        /*************************************************************************
        Bessel function of second kind of integer order

        Returns Bessel function of order n, where n is a
        (possibly negative) integer.

        The function is evaluated by forward recurrence on
        n, starting with values computed by the routines
        y0() and y1().

        If n = 0 or 1 the routine for y0 or y1 is called
        directly.

        ACCURACY:
                             Absolute error, except relative
                             when y > 1:
        arithmetic   domain     # trials      peak         rms
           IEEE      0, 30       30000       3.4e-15     4.3e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double besselyn(int n,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            int i = 0;
            double a = 0;
            double b = 0;
            double tmp = 0;
            double s = 0;

            s = 1;
            if( n<0 )
            {
                n = -n;
                if( n%2!=0 )
                {
                    s = -1;
                }
            }
            if( n==0 )
            {
                result = bessely0(x, _params);
                return result;
            }
            if( n==1 )
            {
                result = s*bessely1(x, _params);
                return result;
            }
            a = bessely0(x, _params);
            b = bessely1(x, _params);
            for(i=1; i<=n-1; i++)
            {
                tmp = b;
                b = 2*i/x*b-a;
                a = tmp;
            }
            result = s*b;
            return result;
        }


        /*************************************************************************
        Modified Bessel function of order zero

        Returns modified Bessel function of order zero of the
        argument.

        The function is defined as i0(x) = j0( ix ).

        The range is partitioned into the two intervals [0,8] and
        (8, infinity).  Chebyshev polynomial expansions are employed
        in each interval.

        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE      0,30        30000       5.8e-16     1.4e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double besseli0(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double y = 0;
            double v = 0;
            double z = 0;
            double b0 = 0;
            double b1 = 0;
            double b2 = 0;

            if( (double)(x)<(double)(0) )
            {
                x = -x;
            }
            if( (double)(x)<=(double)(8.0) )
            {
                y = x/2.0-2.0;
                besselmfirstcheb(-4.41534164647933937950E-18, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 3.33079451882223809783E-17, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -2.43127984654795469359E-16, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 1.71539128555513303061E-15, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -1.16853328779934516808E-14, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 7.67618549860493561688E-14, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -4.85644678311192946090E-13, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 2.95505266312963983461E-12, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -1.72682629144155570723E-11, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 9.67580903537323691224E-11, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -5.18979560163526290666E-10, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 2.65982372468238665035E-9, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -1.30002500998624804212E-8, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 6.04699502254191894932E-8, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -2.67079385394061173391E-7, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 1.11738753912010371815E-6, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -4.41673835845875056359E-6, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 1.64484480707288970893E-5, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -5.75419501008210370398E-5, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 1.88502885095841655729E-4, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -5.76375574538582365885E-4, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 1.63947561694133579842E-3, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -4.32430999505057594430E-3, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 1.05464603945949983183E-2, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -2.37374148058994688156E-2, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 4.93052842396707084878E-2, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -9.49010970480476444210E-2, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 1.71620901522208775349E-1, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -3.04682672343198398683E-1, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 6.76795274409476084995E-1, ref b0, ref b1, ref b2, _params);
                v = 0.5*(b0-b2);
                result = Math.Exp(x)*v;
                return result;
            }
            z = 32.0/x-2.0;
            besselmfirstcheb(-7.23318048787475395456E-18, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, -4.83050448594418207126E-18, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 4.46562142029675999901E-17, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 3.46122286769746109310E-17, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, -2.82762398051658348494E-16, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, -3.42548561967721913462E-16, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 1.77256013305652638360E-15, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 3.81168066935262242075E-15, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, -9.55484669882830764870E-15, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, -4.15056934728722208663E-14, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 1.54008621752140982691E-14, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 3.85277838274214270114E-13, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 7.18012445138366623367E-13, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, -1.79417853150680611778E-12, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, -1.32158118404477131188E-11, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, -3.14991652796324136454E-11, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 1.18891471078464383424E-11, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 4.94060238822496958910E-10, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 3.39623202570838634515E-9, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 2.26666899049817806459E-8, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 2.04891858946906374183E-7, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 2.89137052083475648297E-6, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 6.88975834691682398426E-5, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 3.36911647825569408990E-3, ref b0, ref b1, ref b2, _params);
            besselmnextcheb(z, 8.04490411014108831608E-1, ref b0, ref b1, ref b2, _params);
            v = 0.5*(b0-b2);
            result = Math.Exp(x)*v/Math.Sqrt(x);
            return result;
        }


        /*************************************************************************
        Modified Bessel function of order one

        Returns modified Bessel function of order one of the
        argument.

        The function is defined as i1(x) = -i j1( ix ).

        The range is partitioned into the two intervals [0,8] and
        (8, infinity).  Chebyshev polynomial expansions are employed
        in each interval.

        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE      0, 30       30000       1.9e-15     2.1e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1985, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double besseli1(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double y = 0;
            double z = 0;
            double v = 0;
            double b0 = 0;
            double b1 = 0;
            double b2 = 0;

            z = Math.Abs(x);
            if( (double)(z)<=(double)(8.0) )
            {
                y = z/2.0-2.0;
                besselm1firstcheb(2.77791411276104639959E-18, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -2.11142121435816608115E-17, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 1.55363195773620046921E-16, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.10559694773538630805E-15, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 7.60068429473540693410E-15, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -5.04218550472791168711E-14, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 3.22379336594557470981E-13, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.98397439776494371520E-12, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 1.17361862988909016308E-11, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -6.66348972350202774223E-11, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 3.62559028155211703701E-10, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.88724975172282928790E-9, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 9.38153738649577178388E-9, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -4.44505912879632808065E-8, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 2.00329475355213526229E-7, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -8.56872026469545474066E-7, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 3.47025130813767847674E-6, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.32731636560394358279E-5, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 4.78156510755005422638E-5, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.61760815825896745588E-4, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 5.12285956168575772895E-4, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.51357245063125314899E-3, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 4.15642294431288815669E-3, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.05640848946261981558E-2, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 2.47264490306265168283E-2, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -5.29459812080949914269E-2, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 1.02643658689847095384E-1, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.76416518357834055153E-1, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 2.52587186443633654823E-1, ref b0, ref b1, ref b2, _params);
                v = 0.5*(b0-b2);
                z = v*z*Math.Exp(z);
            }
            else
            {
                y = 32.0/z-2.0;
                besselm1firstcheb(7.51729631084210481353E-18, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 4.41434832307170791151E-18, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -4.65030536848935832153E-17, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -3.20952592199342395980E-17, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 2.96262899764595013876E-16, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 3.30820231092092828324E-16, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.88035477551078244854E-15, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -3.81440307243700780478E-15, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 1.04202769841288027642E-14, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 4.27244001671195135429E-14, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -2.10154184277266431302E-14, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -4.08355111109219731823E-13, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -7.19855177624590851209E-13, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 2.03562854414708950722E-12, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 1.41258074366137813316E-11, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 3.25260358301548823856E-11, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.89749581235054123450E-11, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -5.58974346219658380687E-10, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -3.83538038596423702205E-9, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -2.63146884688951950684E-8, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -2.51223623787020892529E-7, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -3.88256480887769039346E-6, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.10588938762623716291E-4, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -9.76109749136146840777E-3, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 7.78576235018280120474E-1, ref b0, ref b1, ref b2, _params);
                v = 0.5*(b0-b2);
                z = v*Math.Exp(z)/Math.Sqrt(z);
            }
            if( (double)(x)<(double)(0) )
            {
                z = -z;
            }
            result = z;
            return result;
        }


        /*************************************************************************
        Modified Bessel function, second kind, order zero

        Returns modified Bessel function of the second kind
        of order zero of the argument.

        The range is partitioned into the two intervals [0,8] and
        (8, infinity).  Chebyshev polynomial expansions are employed
        in each interval.

        ACCURACY:

        Tested at 2000 random points between 0 and 8.  Peak absolute
        error (relative when K0 > 1) was 1.46e-14; rms, 4.26e-15.
                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE      0, 30       30000       1.2e-15     1.6e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double besselk0(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double y = 0;
            double z = 0;
            double v = 0;
            double b0 = 0;
            double b1 = 0;
            double b2 = 0;

            alglib.ap.assert((double)(x)>(double)(0), "Domain error in BesselK0: x<=0");
            if( (double)(x)<=(double)(2) )
            {
                y = x*x-2.0;
                besselmfirstcheb(1.37446543561352307156E-16, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 4.25981614279661018399E-14, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 1.03496952576338420167E-11, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 1.90451637722020886025E-9, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 2.53479107902614945675E-7, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 2.28621210311945178607E-5, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 1.26461541144692592338E-3, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 3.59799365153615016266E-2, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, 3.44289899924628486886E-1, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(y, -5.35327393233902768720E-1, ref b0, ref b1, ref b2, _params);
                v = 0.5*(b0-b2);
                v = v-Math.Log(0.5*x)*besseli0(x, _params);
            }
            else
            {
                z = 8.0/x-2.0;
                besselmfirstcheb(5.30043377268626276149E-18, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -1.64758043015242134646E-17, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 5.21039150503902756861E-17, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -1.67823109680541210385E-16, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 5.51205597852431940784E-16, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -1.84859337734377901440E-15, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 6.34007647740507060557E-15, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -2.22751332699166985548E-14, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 8.03289077536357521100E-14, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -2.98009692317273043925E-13, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 1.14034058820847496303E-12, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -4.51459788337394416547E-12, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 1.85594911495471785253E-11, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -7.95748924447710747776E-11, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 3.57739728140030116597E-10, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -1.69753450938905987466E-9, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 8.57403401741422608519E-9, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -4.66048989768794782956E-8, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 2.76681363944501510342E-7, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -1.83175552271911948767E-6, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 1.39498137188764993662E-5, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -1.28495495816278026384E-4, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 1.56988388573005337491E-3, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, -3.14481013119645005427E-2, ref b0, ref b1, ref b2, _params);
                besselmnextcheb(z, 2.44030308206595545468E0, ref b0, ref b1, ref b2, _params);
                v = 0.5*(b0-b2);
                v = v*Math.Exp(-x)/Math.Sqrt(x);
            }
            result = v;
            return result;
        }


        /*************************************************************************
        Modified Bessel function, second kind, order one

        Computes the modified Bessel function of the second kind
        of order one of the argument.

        The range is partitioned into the two intervals [0,2] and
        (2, infinity).  Chebyshev polynomial expansions are employed
        in each interval.

        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE      0, 30       30000       1.2e-15     1.6e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double besselk1(double x,
            alglib.xparams _params)
        {
            double result = 0;
            double y = 0;
            double z = 0;
            double v = 0;
            double b0 = 0;
            double b1 = 0;
            double b2 = 0;

            z = 0.5*x;
            alglib.ap.assert((double)(z)>(double)(0), "Domain error in K1");
            if( (double)(x)<=(double)(2) )
            {
                y = x*x-2.0;
                besselm1firstcheb(-7.02386347938628759343E-18, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -2.42744985051936593393E-15, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -6.66690169419932900609E-13, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.41148839263352776110E-10, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -2.21338763073472585583E-8, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -2.43340614156596823496E-6, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.73028895751305206302E-4, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -6.97572385963986435018E-3, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.22611180822657148235E-1, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -3.53155960776544875667E-1, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 1.52530022733894777053E0, ref b0, ref b1, ref b2, _params);
                v = 0.5*(b0-b2);
                result = Math.Log(z)*besseli1(x, _params)+v/x;
            }
            else
            {
                y = 8.0/x-2.0;
                besselm1firstcheb(-5.75674448366501715755E-18, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 1.79405087314755922667E-17, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -5.68946255844285935196E-17, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 1.83809354436663880070E-16, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -6.05704724837331885336E-16, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 2.03870316562433424052E-15, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -7.01983709041831346144E-15, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 2.47715442448130437068E-14, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -8.97670518232499435011E-14, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 3.34841966607842919884E-13, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.28917396095102890680E-12, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 5.13963967348173025100E-12, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -2.12996783842756842877E-11, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 9.21831518760500529508E-11, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -4.19035475934189648750E-10, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 2.01504975519703286596E-9, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.03457624656780970260E-8, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 5.74108412545004946722E-8, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -3.50196060308781257119E-7, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 2.40648494783721712015E-6, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -1.93619797416608296024E-5, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 1.95215518471351631108E-4, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, -2.85781685962277938680E-3, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 1.03923736576817238437E-1, ref b0, ref b1, ref b2, _params);
                besselm1nextcheb(y, 2.72062619048444266945E0, ref b0, ref b1, ref b2, _params);
                v = 0.5*(b0-b2);
                result = Math.Exp(-x)*v/Math.Sqrt(x);
            }
            return result;
        }


        /*************************************************************************
        Modified Bessel function, second kind, integer order

        Returns modified Bessel function of the second kind
        of order n of the argument.

        The range is partitioned into the two intervals [0,9.55] and
        (9.55, infinity).  An ascending power series is used in the
        low range, and an asymptotic expansion in the high range.

        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE      0,30        90000       1.8e-8      3.0e-10

        Error is high only near the crossover point x = 9.55
        between the two expansions used.

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1988, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double besselkn(int nn,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double k = 0;
            double kf = 0;
            double nk1f = 0;
            double nkf = 0;
            double zn = 0;
            double t = 0;
            double s = 0;
            double z0 = 0;
            double z = 0;
            double ans = 0;
            double fn = 0;
            double pn = 0;
            double pk = 0;
            double zmn = 0;
            double tlg = 0;
            double tox = 0;
            int i = 0;
            int n = 0;
            double eul = 0;

            eul = 5.772156649015328606065e-1;
            if( nn<0 )
            {
                n = -nn;
            }
            else
            {
                n = nn;
            }
            alglib.ap.assert(n<=31, "Overflow in BesselKN");
            alglib.ap.assert((double)(x)>(double)(0), "Domain error in BesselKN");
            if( (double)(x)<=(double)(9.55) )
            {
                ans = 0.0;
                z0 = 0.25*x*x;
                fn = 1.0;
                pn = 0.0;
                zmn = 1.0;
                tox = 2.0/x;
                if( n>0 )
                {
                    pn = -eul;
                    k = 1.0;
                    for(i=1; i<=n-1; i++)
                    {
                        pn = pn+1.0/k;
                        k = k+1.0;
                        fn = fn*k;
                    }
                    zmn = tox;
                    if( n==1 )
                    {
                        ans = 1.0/x;
                    }
                    else
                    {
                        nk1f = fn/n;
                        kf = 1.0;
                        s = nk1f;
                        z = -z0;
                        zn = 1.0;
                        for(i=1; i<=n-1; i++)
                        {
                            nk1f = nk1f/(n-i);
                            kf = kf*i;
                            zn = zn*z;
                            t = nk1f*zn/kf;
                            s = s+t;
                            alglib.ap.assert((double)(math.maxrealnumber-Math.Abs(t))>(double)(Math.Abs(s)), "Overflow in BesselKN");
                            alglib.ap.assert(!((double)(tox)>(double)(1.0) && (double)(math.maxrealnumber/tox)<(double)(zmn)), "Overflow in BesselKN");
                            zmn = zmn*tox;
                        }
                        s = s*0.5;
                        t = Math.Abs(s);
                        alglib.ap.assert(!((double)(zmn)>(double)(1.0) && (double)(math.maxrealnumber/zmn)<(double)(t)), "Overflow in BesselKN");
                        alglib.ap.assert(!((double)(t)>(double)(1.0) && (double)(math.maxrealnumber/t)<(double)(zmn)), "Overflow in BesselKN");
                        ans = s*zmn;
                    }
                }
                tlg = 2.0*Math.Log(0.5*x);
                pk = -eul;
                if( n==0 )
                {
                    pn = pk;
                    t = 1.0;
                }
                else
                {
                    pn = pn+1.0/n;
                    t = 1.0/fn;
                }
                s = (pk+pn-tlg)*t;
                k = 1.0;
                do
                {
                    t = t*(z0/(k*(k+n)));
                    pk = pk+1.0/k;
                    pn = pn+1.0/(k+n);
                    s = s+(pk+pn-tlg)*t;
                    k = k+1.0;
                }
                while( (double)(Math.Abs(t/s))>(double)(math.machineepsilon) );
                s = 0.5*s/zmn;
                if( n%2!=0 )
                {
                    s = -s;
                }
                ans = ans+s;
                result = ans;
                return result;
            }
            if( (double)(x)>(double)(Math.Log(math.maxrealnumber)) )
            {
                result = 0;
                return result;
            }
            k = n;
            pn = 4.0*k*k;
            pk = 1.0;
            z0 = 8.0*x;
            fn = 1.0;
            t = 1.0;
            s = t;
            nkf = math.maxrealnumber;
            i = 0;
            do
            {
                z = pn-pk*pk;
                t = t*z/(fn*z0);
                nk1f = Math.Abs(t);
                if( i>=n && (double)(nk1f)>(double)(nkf) )
                {
                    break;
                }
                nkf = nk1f;
                s = s+t;
                fn = fn+1.0;
                pk = pk+2.0;
                i = i+1;
            }
            while( (double)(Math.Abs(t/s))>(double)(math.machineepsilon) );
            result = Math.Exp(-x)*Math.Sqrt(Math.PI/(2.0*x))*s;
            return result;
        }


        /*************************************************************************
        Internal subroutine

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        private static void besselmfirstcheb(double c,
            ref double b0,
            ref double b1,
            ref double b2,
            alglib.xparams _params)
        {
            b0 = c;
            b1 = 0.0;
            b2 = 0.0;
        }


        /*************************************************************************
        Internal subroutine

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        private static void besselmnextcheb(double x,
            double c,
            ref double b0,
            ref double b1,
            ref double b2,
            alglib.xparams _params)
        {
            b2 = b1;
            b1 = b0;
            b0 = x*b1-b2+c;
        }


        /*************************************************************************
        Internal subroutine

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        private static void besselm1firstcheb(double c,
            ref double b0,
            ref double b1,
            ref double b2,
            alglib.xparams _params)
        {
            b0 = c;
            b1 = 0.0;
            b2 = 0.0;
        }


        /*************************************************************************
        Internal subroutine

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        private static void besselm1nextcheb(double x,
            double c,
            ref double b0,
            ref double b1,
            ref double b2,
            alglib.xparams _params)
        {
            b2 = b1;
            b1 = b0;
            b0 = x*b1-b2+c;
        }


        private static void besselasympt0(double x,
            ref double pzero,
            ref double qzero,
            alglib.xparams _params)
        {
            double xsq = 0;
            double p2 = 0;
            double q2 = 0;
            double p3 = 0;
            double q3 = 0;

            pzero = 0;
            qzero = 0;

            xsq = 64.0/(x*x);
            p2 = 0.0;
            p2 = 2485.271928957404011288128951+xsq*p2;
            p2 = 153982.6532623911470917825993+xsq*p2;
            p2 = 2016135.283049983642487182349+xsq*p2;
            p2 = 8413041.456550439208464315611+xsq*p2;
            p2 = 12332384.76817638145232406055+xsq*p2;
            p2 = 5393485.083869438325262122897+xsq*p2;
            q2 = 1.0;
            q2 = 2615.700736920839685159081813+xsq*q2;
            q2 = 156001.7276940030940592769933+xsq*q2;
            q2 = 2025066.801570134013891035236+xsq*q2;
            q2 = 8426449.050629797331554404810+xsq*q2;
            q2 = 12338310.22786324960844856182+xsq*q2;
            q2 = 5393485.083869438325560444960+xsq*q2;
            p3 = -0.0;
            p3 = -4.887199395841261531199129300+xsq*p3;
            p3 = -226.2630641933704113967255053+xsq*p3;
            p3 = -2365.956170779108192723612816+xsq*p3;
            p3 = -8239.066313485606568803548860+xsq*p3;
            p3 = -10381.41698748464093880530341+xsq*p3;
            p3 = -3984.617357595222463506790588+xsq*p3;
            q3 = 1.0;
            q3 = 408.7714673983499223402830260+xsq*q3;
            q3 = 15704.89191515395519392882766+xsq*q3;
            q3 = 156021.3206679291652539287109+xsq*q3;
            q3 = 533291.3634216897168722255057+xsq*q3;
            q3 = 666745.4239319826986004038103+xsq*q3;
            q3 = 255015.5108860942382983170882+xsq*q3;
            pzero = p2/q2;
            qzero = 8*p3/q3/x;
        }


        private static void besselasympt1(double x,
            ref double pzero,
            ref double qzero,
            alglib.xparams _params)
        {
            double xsq = 0;
            double p2 = 0;
            double q2 = 0;
            double p3 = 0;
            double q3 = 0;

            pzero = 0;
            qzero = 0;

            xsq = 64.0/(x*x);
            p2 = -1611.616644324610116477412898;
            p2 = -109824.0554345934672737413139+xsq*p2;
            p2 = -1523529.351181137383255105722+xsq*p2;
            p2 = -6603373.248364939109255245434+xsq*p2;
            p2 = -9942246.505077641195658377899+xsq*p2;
            p2 = -4435757.816794127857114720794+xsq*p2;
            q2 = 1.0;
            q2 = -1455.009440190496182453565068+xsq*q2;
            q2 = -107263.8599110382011903063867+xsq*q2;
            q2 = -1511809.506634160881644546358+xsq*q2;
            q2 = -6585339.479723087072826915069+xsq*q2;
            q2 = -9934124.389934585658967556309+xsq*q2;
            q2 = -4435757.816794127856828016962+xsq*q2;
            p3 = 35.26513384663603218592175580;
            p3 = 1706.375429020768002061283546+xsq*p3;
            p3 = 18494.26287322386679652009819+xsq*p3;
            p3 = 66178.83658127083517939992166+xsq*p3;
            p3 = 85145.16067533570196555001171+xsq*p3;
            p3 = 33220.91340985722351859704442+xsq*p3;
            q3 = 1.0;
            q3 = 863.8367769604990967475517183+xsq*q3;
            q3 = 37890.22974577220264142952256+xsq*q3;
            q3 = 400294.4358226697511708610813+xsq*q3;
            q3 = 1419460.669603720892855755253+xsq*q3;
            q3 = 1819458.042243997298924553839+xsq*q3;
            q3 = 708712.8194102874357377502472+xsq*q3;
            pzero = p2/q2;
            qzero = 8*p3/q3/x;
        }


    }
    public class laguerre
    {
        /*************************************************************************
        Calculation of the value of the Laguerre polynomial.

        Parameters:
            n   -   degree, n>=0
            x   -   argument

        Result:
            the value of the Laguerre polynomial Ln at x
        *************************************************************************/
        public static double laguerrecalculate(int n,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double a = 0;
            double b = 0;
            double i = 0;

            result = 1;
            a = 1;
            b = 1-x;
            if( n==1 )
            {
                result = b;
            }
            i = 2;
            while( (double)(i)<=(double)(n) )
            {
                result = ((2*i-1-x)*b-(i-1)*a)/i;
                a = b;
                b = result;
                i = i+1;
            }
            return result;
        }


        /*************************************************************************
        Summation of Laguerre polynomials using Clenshaw's recurrence formula.

        This routine calculates c[0]*L0(x) + c[1]*L1(x) + ... + c[N]*LN(x)

        Parameters:
            n   -   degree, n>=0
            x   -   argument

        Result:
            the value of the Laguerre polynomial at x
        *************************************************************************/
        public static double laguerresum(double[] c,
            int n,
            double x,
            alglib.xparams _params)
        {
            double result = 0;
            double b1 = 0;
            double b2 = 0;
            int i = 0;

            b1 = 0;
            b2 = 0;
            result = 0;
            for(i=n; i>=0; i--)
            {
                result = (2*i+1-x)*b1/(i+1)-(i+1)*b2/(i+2)+c[i];
                b2 = b1;
                b1 = result;
            }
            return result;
        }


        /*************************************************************************
        Representation of Ln as C[0] + C[1]*X + ... + C[N]*X^N

        Input parameters:
            N   -   polynomial degree, n>=0

        Output parameters:
            C   -   coefficients
        *************************************************************************/
        public static void laguerrecoefficients(int n,
            ref double[] c,
            alglib.xparams _params)
        {
            int i = 0;

            c = new double[0];

            c = new double[n+1];
            c[0] = 1;
            for(i=0; i<=n-1; i++)
            {
                c[i+1] = -(c[i]*(n-i)/(i+1)/(i+1));
            }
        }


    }
    public class elliptic
    {
        /*************************************************************************
        Complete elliptic integral of the first kind

        Approximates the integral



                   pi/2
                    -
                   | |
                   |           dt
        K(m)  =    |    ------------------
                   |                   2
                 | |    sqrt( 1 - m sin t )
                  -
                   0

        using the approximation

            P(x)  -  log x Q(x).

        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE       0,1        30000       2.5e-16     6.8e-17

        Cephes Math Library, Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double ellipticintegralk(double m,
            alglib.xparams _params)
        {
            double result = 0;

            result = ellipticintegralkhighprecision(1.0-m, _params);
            return result;
        }


        /*************************************************************************
        Complete elliptic integral of the first kind

        Approximates the integral



                   pi/2
                    -
                   | |
                   |           dt
        K(m)  =    |    ------------------
                   |                   2
                 | |    sqrt( 1 - m sin t )
                  -
                   0

        where m = 1 - m1, using the approximation

            P(x)  -  log x Q(x).

        The argument m1 is used rather than m so that the logarithmic
        singularity at m = 1 will be shifted to the origin; this
        preserves maximum accuracy.

        K(0) = pi/2.

        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE       0,1        30000       2.5e-16     6.8e-17

        Cephes Math Library, Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double ellipticintegralkhighprecision(double m1,
            alglib.xparams _params)
        {
            double result = 0;
            double p = 0;
            double q = 0;

            if( (double)(m1)<=(double)(math.machineepsilon) )
            {
                result = 1.3862943611198906188E0-0.5*Math.Log(m1);
            }
            else
            {
                p = 1.37982864606273237150E-4;
                p = p*m1+2.28025724005875567385E-3;
                p = p*m1+7.97404013220415179367E-3;
                p = p*m1+9.85821379021226008714E-3;
                p = p*m1+6.87489687449949877925E-3;
                p = p*m1+6.18901033637687613229E-3;
                p = p*m1+8.79078273952743772254E-3;
                p = p*m1+1.49380448916805252718E-2;
                p = p*m1+3.08851465246711995998E-2;
                p = p*m1+9.65735902811690126535E-2;
                p = p*m1+1.38629436111989062502E0;
                q = 2.94078955048598507511E-5;
                q = q*m1+9.14184723865917226571E-4;
                q = q*m1+5.94058303753167793257E-3;
                q = q*m1+1.54850516649762399335E-2;
                q = q*m1+2.39089602715924892727E-2;
                q = q*m1+3.01204715227604046988E-2;
                q = q*m1+3.73774314173823228969E-2;
                q = q*m1+4.88280347570998239232E-2;
                q = q*m1+7.03124996963957469739E-2;
                q = q*m1+1.24999999999870820058E-1;
                q = q*m1+4.99999999999999999821E-1;
                result = p-q*Math.Log(m1);
            }
            return result;
        }


        /*************************************************************************
        Incomplete elliptic integral of the first kind F(phi|m)

        Approximates the integral



                       phi
                        -
                       | |
                       |           dt
        F(phi_\m)  =    |    ------------------
                       |                   2
                     | |    sqrt( 1 - m sin t )
                      -
                       0

        of amplitude phi and modulus m, using the arithmetic -
        geometric mean algorithm.




        ACCURACY:

        Tested at random points with m in [0, 1] and phi as indicated.

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE     -10,10       200000      7.4e-16     1.0e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double incompleteellipticintegralk(double phi,
            double m,
            alglib.xparams _params)
        {
            double result = 0;
            double a = 0;
            double b = 0;
            double c = 0;
            double e = 0;
            double temp = 0;
            double pio2 = 0;
            double t = 0;
            double k = 0;
            int d = 0;
            int md = 0;
            int s = 0;
            int npio2 = 0;

            pio2 = 1.57079632679489661923;
            if( (double)(m)==(double)(0) )
            {
                result = phi;
                return result;
            }
            a = 1-m;
            if( (double)(a)==(double)(0) )
            {
                result = Math.Log(Math.Tan(0.5*(pio2+phi)));
                return result;
            }
            npio2 = (int)Math.Floor(phi/pio2);
            if( npio2%2!=0 )
            {
                npio2 = npio2+1;
            }
            if( npio2!=0 )
            {
                k = ellipticintegralk(1-a, _params);
                phi = phi-npio2*pio2;
            }
            else
            {
                k = 0;
            }
            if( (double)(phi)<(double)(0) )
            {
                phi = -phi;
                s = -1;
            }
            else
            {
                s = 0;
            }
            b = Math.Sqrt(a);
            t = Math.Tan(phi);
            if( (double)(Math.Abs(t))>(double)(10) )
            {
                e = 1.0/(b*t);
                if( (double)(Math.Abs(e))<(double)(10) )
                {
                    e = Math.Atan(e);
                    if( npio2==0 )
                    {
                        k = ellipticintegralk(1-a, _params);
                    }
                    temp = k-incompleteellipticintegralk(e, m, _params);
                    if( s<0 )
                    {
                        temp = -temp;
                    }
                    result = temp+npio2*k;
                    return result;
                }
            }
            a = 1.0;
            c = Math.Sqrt(m);
            d = 1;
            md = 0;
            while( (double)(Math.Abs(c/a))>(double)(math.machineepsilon) )
            {
                temp = b/a;
                phi = phi+Math.Atan(t*temp)+md*Math.PI;
                md = (int)((phi+pio2)/Math.PI);
                t = t*(1.0+temp)/(1.0-temp*t*t);
                c = 0.5*(a-b);
                temp = Math.Sqrt(a*b);
                a = 0.5*(a+b);
                b = temp;
                d = d+d;
            }
            temp = (Math.Atan(t)+md*Math.PI)/(d*a);
            if( s<0 )
            {
                temp = -temp;
            }
            result = temp+npio2*k;
            return result;
        }


        /*************************************************************************
        Complete elliptic integral of the second kind

        Approximates the integral


                   pi/2
                    -
                   | |                 2
        E(m)  =    |    sqrt( 1 - m sin t ) dt
                 | |
                  -
                   0

        using the approximation

             P(x)  -  x log x Q(x).

        ACCURACY:

                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE       0, 1       10000       2.1e-16     7.3e-17

        Cephes Math Library, Release 2.8: June, 2000
        Copyright 1984, 1987, 1989, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double ellipticintegrale(double m,
            alglib.xparams _params)
        {
            double result = 0;
            double p = 0;
            double q = 0;

            alglib.ap.assert((double)(m)>=(double)(0) && (double)(m)<=(double)(1), "Domain error in EllipticIntegralE: m<0 or m>1");
            m = 1-m;
            if( (double)(m)==(double)(0) )
            {
                result = 1;
                return result;
            }
            p = 1.53552577301013293365E-4;
            p = p*m+2.50888492163602060990E-3;
            p = p*m+8.68786816565889628429E-3;
            p = p*m+1.07350949056076193403E-2;
            p = p*m+7.77395492516787092951E-3;
            p = p*m+7.58395289413514708519E-3;
            p = p*m+1.15688436810574127319E-2;
            p = p*m+2.18317996015557253103E-2;
            p = p*m+5.68051945617860553470E-2;
            p = p*m+4.43147180560990850618E-1;
            p = p*m+1.00000000000000000299E0;
            q = 3.27954898576485872656E-5;
            q = q*m+1.00962792679356715133E-3;
            q = q*m+6.50609489976927491433E-3;
            q = q*m+1.68862163993311317300E-2;
            q = q*m+2.61769742454493659583E-2;
            q = q*m+3.34833904888224918614E-2;
            q = q*m+4.27180926518931511717E-2;
            q = q*m+5.85936634471101055642E-2;
            q = q*m+9.37499997197644278445E-2;
            q = q*m+2.49999999999888314361E-1;
            result = p-q*m*Math.Log(m);
            return result;
        }


        /*************************************************************************
        Incomplete elliptic integral of the second kind

        Approximates the integral


                       phi
                        -
                       | |
                       |                   2
        E(phi_\m)  =    |    sqrt( 1 - m sin t ) dt
                       |
                     | |
                      -
                       0

        of amplitude phi and modulus m, using the arithmetic -
        geometric mean algorithm.

        ACCURACY:

        Tested at random arguments with phi in [-10, 10] and m in
        [0, 1].
                             Relative error:
        arithmetic   domain     # trials      peak         rms
           IEEE     -10,10      150000       3.3e-15     1.4e-16

        Cephes Math Library Release 2.8:  June, 2000
        Copyright 1984, 1987, 1993, 2000 by Stephen L. Moshier
        *************************************************************************/
        public static double incompleteellipticintegrale(double phi,
            double m,
            alglib.xparams _params)
        {
            double result = 0;
            double pio2 = 0;
            double a = 0;
            double b = 0;
            double c = 0;
            double e = 0;
            double temp = 0;
            double lphi = 0;
            double t = 0;
            double ebig = 0;
            int d = 0;
            int md = 0;
            int npio2 = 0;
            int s = 0;

            pio2 = 1.57079632679489661923;
            if( (double)(m)==(double)(0) )
            {
                result = phi;
                return result;
            }
            lphi = phi;
            npio2 = (int)Math.Floor(lphi/pio2);
            if( npio2%2!=0 )
            {
                npio2 = npio2+1;
            }
            lphi = lphi-npio2*pio2;
            if( (double)(lphi)<(double)(0) )
            {
                lphi = -lphi;
                s = -1;
            }
            else
            {
                s = 1;
            }
            a = 1.0-m;
            ebig = ellipticintegrale(m, _params);
            if( (double)(a)==(double)(0) )
            {
                temp = Math.Sin(lphi);
                if( s<0 )
                {
                    temp = -temp;
                }
                result = temp+npio2*ebig;
                return result;
            }
            t = Math.Tan(lphi);
            b = Math.Sqrt(a);
            
            //
            // Thanks to Brian Fitzgerald <fitzgb@mml0.meche.rpi.edu>
            // for pointing out an instability near odd multiples of pi/2
            //
            if( (double)(Math.Abs(t))>(double)(10) )
            {
                
                //
                // Transform the amplitude
                //
                e = 1.0/(b*t);
                
                //
                // ... but avoid multiple recursions.
                //
                if( (double)(Math.Abs(e))<(double)(10) )
                {
                    e = Math.Atan(e);
                    temp = ebig+m*Math.Sin(lphi)*Math.Sin(e)-incompleteellipticintegrale(e, m, _params);
                    if( s<0 )
                    {
                        temp = -temp;
                    }
                    result = temp+npio2*ebig;
                    return result;
                }
            }
            c = Math.Sqrt(m);
            a = 1.0;
            d = 1;
            e = 0.0;
            md = 0;
            while( (double)(Math.Abs(c/a))>(double)(math.machineepsilon) )
            {
                temp = b/a;
                lphi = lphi+Math.Atan(t*temp)+md*Math.PI;
                md = (int)((lphi+pio2)/Math.PI);
                t = t*(1.0+temp)/(1.0-temp*t*t);
                c = 0.5*(a-b);
                temp = Math.Sqrt(a*b);
                a = 0.5*(a+b);
                b = temp;
                d = d+d;
                e = e+c*Math.Sin(lphi);
            }
            temp = ebig/ellipticintegralk(m, _params);
            temp = temp*((Math.Atan(t)+md*Math.PI)/(d*a));
            temp = temp+e;
            if( s<0 )
            {
                temp = -temp;
            }
            result = temp+npio2*ebig;
            return result;
        }


    }
}