version 1.0

DESCRIPTION

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+Package: unifed
+Title: The Unifed Distribution
+Version: 1.0
+Date: 2018-12-23
+Description: Introduced in Quijano Xacur (2018) <arXiv:1812.00251>. This package contains the density, distribution, quantile and random generation functions for the unifed. It also contains functions for the unifed family and quasifamily that can be used with the glm() function.
+Depends: R (>= 3.1), methods
+License: GPL (>= 3)
+Encoding: UTF-8
+LazyData: true
+RoxygenNote: 6.1.0
+Suggests: knitr, rmarkdown
+VignetteBuilder: knitr
+Author: Oscar Alberto Quijano Xacur [aut,cre]
+Maintainer: Oscar Alberto Quijano Xacur <oscar.quijano@use.startmail.com>
+NeedsCompilation: yes
+Packaged: 2019-01-21 15:22:43 UTC; oscar
+Repository: CRAN
+Date/Publication: 2019-01-30 18:40:03 UTC

MD5

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+af487460752a22d74f19513d7fd9f154 *DESCRIPTION
+1f14593fdae9328057e53441f20653e6 *NAMESPACE
+dfa125ee5b266fd3e2a47a8da47bcfa1 *R/dirwin.hall.R
+f2757132e44a7e2fc86e494e140e2fed *R/dunifed.R
+e67fa11806ca3c759ac56553bd1f664c *R/summary_unifed_glm.R
+9df00b055204c5756274f0044d4d9d74 *R/unifed.R
+0fae5502964b42527b1f3ac3bd2146c3 *R/unifed.deviance.R
+37e825f06579b4b2c758bcc6851d0cf0 *R/unifed.kappa.R
+7aa7d160accd44e2bc4ca44adc6de39c *R/unifed.varf.R
+d107da57f8fd4f8b5461dfda55901508 *R/zzz.R
+8b88335e4b660ccd759564cc8fea7e33 *README.md
+73aa477ccf3c7c59b857abc15da79794 *build/vignette.rds
+0e57fd2f8b9ca3806b35e9e2b0164b97 *inst/doc/introduction_unifed.R
+4e130758dd6d12318c4e24a57f9243ef *inst/doc/introduction_unifed.Rmd
+6a45287d7991e5e06b634ab5956a13e0 *inst/doc/introduction_unifed.html
+4e8c0a0cc72788425161fc37173b4ea7 *man/dirwin.hall.Rd
+49c483775cff05601eefbaab98435570 *man/dunifed.Rd
+7cfe0eaf19949070341752b444c40cd3 *man/summary_unifed_glm.Rd
+58186ae61b2fb8ae4bc83cfb71eb6ce5 *man/unifed.Rd
+a719316ec3c55cf10b08485d9d720ed5 *man/unifed.deviance.Rd
+52832a88b93e87a388a99e873aa242f7 *man/unifed.kappa.Rd
+fdbfca941463b82b7350772ab5fbabed *man/unifed.varf.Rd
+217241e5407ed733438f7f3c6c0b5027 *src/unifed_kappa.c
+2d8ce114754786b08468d15627a48cf0 *vignettes/bibliography.bib
+aaaa8f6d17f32b4d0976394b3e7f23ec *vignettes/introduction_unifed.Rmd

NAMESPACE

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+# Generated by roxygen2: do not edit by hand
+
+export(dirwin.hall)
+export(dunifed)
+export(punifed)
+export(quasiunifed)
+export(qunifed)
+export(runifed)
+export(summary_unifed_glm)
+export(unifed)
+export(unifed.deviance)
+export(unifed.kappa)
+export(unifed.kappa.double.prime)
+export(unifed.kappa.prime)
+export(unifed.kappa.prime.inverse)
+export(unifed.kappa.prime.inverse.one)
+export(unifed.unit.deviance)
+export(unifed.varf)
+importFrom(methods,setMethod)
+importFrom(stats,make.link)
+importFrom(stats,runif)
+useDynLib(unifed,unifed_kappa)
+useDynLib(unifed,unifed_kappa_prime_inverse)
+useDynLib(unifed,unit_deviance)

R/dirwin.hall.R

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+#' Irwin-Hall density
+#'
+#' @param x A number between 0 and \code{n}.
+#'
+#' @param n Number of uniform distributions in the unit interval to sum.
+#'
+#' @param log If it evaluates to \code{TRUE} it returns the log of the
+#' density instead of the density.
+#'
+#' @details Gives the density of the Irwin-Hall distribution. It is
+#'     the density of the sum of \code{n} uniform distributions on the
+#'     interval (0,1).
+#'
+#' \deqn{
+#'   h(y;n) = \frac{1}{(n-1)!}\sum_{k=0}^{ \left\lfloor y \right\rfloor } (-1)^k {n \choose k} (y-k)^{n-1}
+#' }{
+#'                 1       __ |_y_|       k /  n \         n - 1 
+#' h(y;n)  =  ---------  \         ( - 1)   |    |  (y - k)      
+#'             (n - 1)!  /__ k = 0          \ k  /               
+#' }
+#'
+#' where \eqn{x \in [0,1]} and \eqn{n} is a positive integer.
+#'
+#' This function is not numerically stable. The examples have some cases of this.
+#'
+#' @examples
+#'
+#' dirwin.hall(2,5)
+#' 
+#' # Numerically unstable example
+#' # Run the following one after the other
+#' # See how it goes from positive to negative (which means overflowing )
+#' dirwin.hall(35,50)
+#' dirwin.hall(36,50)
+#' dirwin.hall(37,50)
+#' dirwin.hall(38,50)
+#' 
+#' @export
+
+dirwin.hall <- function(x,n,log=FALSE){
+
+    ret1 <- 0
+    if ( x < 0 | x > n)
+        stop("x must be greater or equal to 0 and less or equal to n")
+    for(k in 0:floor(x))
+        ret1 <- ret1+ (-1)^k*choose(n,k)*(x-k)^(n-1)
+    if(log){
+        if( n==1)
+            return( log(ret1) )
+        else
+            return( log(ret1)-sum(log(1:(n-1)))  )
+    }else{
+        if( n==1)
+            return( ret1   )
+        else
+            return( ret1 / (factorial(n-1)) )
+    }
+}

R/dunifed.R

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+#' The unifed distribution
+#'  
+#' @description Density, distribution function, quantile function and
+#'     random generation for the unifed distribution.
+#'
+#' @param x A vector of quantiles. They must be numbers between 0 and 1.
+#'
+#' @param theta The value of the canonical parameter. It must be of length one.
+#'
+#' @return \code{dunifed} gives the density function.
+#'
+#' @references{
+#' Quijano Xacur, Oscar Alberto (2018). The Unifed Distribution. ArXiv. \url{http://arxiv.org/abs/1812.00251}.
+#' 
+#' }
+#'
+#' @examples
+#'
+#' dunifed( c(0.1,0.3,0.7), 10)
+#' 
+#' @export
+dunifed <- function(x,theta){
+    if(length(theta) > 1)
+        stop("thetha must be of length one")
+    ifelse( x < 0 | x > 1,
+           0,
+           exp( x * theta - unifed.kappa(theta) ))
+}
+
+#' @rdname dunifed
+#' @name punifed
+#'
+#' @param q A vector of quantiles.
+#'
+#' @return \code{punifed} gives the distribution function.
+#'
+#' @examples
+#'
+#' x <- c(0.1,0.4,0.7,1)
+#' punifed(x,-5)
+#' 
+#' @export
+punifed <- function(q,theta){
+
+    if(length(theta) > 1)
+        stop("thetha must be of length one")    
+    ret <- numeric(length(q))
+    less.than.zerop <- q<=0
+    greater.than.onep <- q>=1
+    between.zero.and.onep <- !( less.than.zerop  | greater.than.onep )
+    ret[less.than.zerop] <- 0
+    ret[greater.than.onep] <- 1
+
+    if ( abs(theta) <= sqrt(.Machine$double.eps) )
+        ret[ between.zero.and.onep ] <- q[between.zero.and.onep]
+    else{
+        q.subset <- q[between.zero.and.onep]
+        ret[ between.zero.and.onep ] <- ( ( exp(q.subset*theta) -1 )  / ( exp(theta) -1 )  )
+    }
+
+    ret
+}
+
+
+#' @rdname dunifed
+#' @name qunifed
+#'
+#' @param p A vector of probabilities.
+#'
+#' @return \code{qunifed} gives the quantile function.
+#'
+#' @examples
+#'
+#' p <- 1:9/10
+#' qunifed(p,5)
+#' 
+#' @export
+#' 
+qunifed <- function(p,theta){
+    if( T %in% (p<0 | p>1) )
+        stop("The values of p must be a number between 0 and 1")
+    if(length(theta) > 1)
+        stop("thetha must be of length one")
+    if ( abs(theta) <= sqrt(.Machine$double.eps) )
+        p
+    else
+        log(p * ( exp(theta) -1 ) + 1 ) / theta
+
+}
+
+#' @rdname dunifed
+#' @name runifed
+#'
+#' @param n number of observations
+#'
+#' @return \code{runifed} generates random observations.
+#'
+#' @examples
+#'
+#' runifed(20,-3.3)
+#' 
+#' @export 
+runifed <- function(n,theta){
+    qunifed( runif(n) , theta  )
+}
+
+##  LocalWords:  quantile

R/summary_unifed_glm.R

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+#' Summarizing Generalized Linear Model Fits
+#'
+#' Wrapper function for summary.glm.
+#'
+#' @param object an object of class "glm".
+#'
+#' @param ... Other arguments for \code{stats::summary.glm}.
+#' 
+#' This wrapper function was created in order to automatically set to
+#' 1 the dispersion parameter of a fitted unifed GLM. When the package
+#' is loaded the summary method of the glm class is rewritten using
+#' this function.
+#' 
+#' @export 
+summary_unifed_glm<- function(object,...){
+    args.list <- list(...)
+    if( object$family$family=="unifed" &
+        ( !("dispersion" %in% names(args.list)) | is.null(args.list$dispersion)) ){
+        stats::summary.glm(object,dispersion=1,...)
+    }else{
+        stats::summary.glm(object,...)
+    }    
+}