version 1.0.2

DESCRIPTION

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+Package: libstable4u
+Version: 1.0.2
+Date: 2023-07-30
+Title: Stable Distribution Functions...For You
+Authors@R: c(
+  person("Javier", "Royuela del Val", role = c("aut")),
+  person("Federico", "Simmross-Wattenberg", role = "aut"), 
+  person("Carlos", "Alberola López", role = "aut"),
+  person("Bob", "Rudis", role = "ctb", comment = "Several bugs fixed and added macOS compatibility"),
+  person("Bruce", "Swihart", role = c("ctb","cre"), email = "bruce.swihart@gmail.com", comment = "Several bugs fixed and added macOS compatibility"))
+Description: Tools for fast and accurate evaluation of skew stable distributions 
+  (CDF, PDF and quantile functions), random number generation, and parameter 
+  estimation.  This is 'libstableR' as per Royuela del Val, Simmross-Wattenberg, 
+  and Alberola López (2017) <doi:10.18637/jss.v078.i01> under a new maintainer.  
+Author: Javier Royuela del Val [aut],
+  Federico Simmross-Wattenberg [aut],
+  Carlos Alberola López [aut],
+  Bob Rudis [ctb] (Several bugs fixed and added macOS compatibility),
+  Bruce Swihart [ctb, cre] (Several bugs fixed and added macOS
+    compatibility)
+License: GPL-3
+Imports: Rcpp (>= 0.12.9)
+LinkingTo: Rcpp, RcppGSL
+SystemRequirements: GNU GSL
+Encoding: UTF-8
+NeedsCompilation: yes
+Maintainer: Bruce Swihart <bruce.swihart@gmail.com>
+Repository: CRAN
+RoxygenNote: 7.2.1
+Suggests: testthat
+Packaged: 2023-08-11 14:17:32 UTC; bruce
+Date/Publication: 2023-08-14 08:50:02 UTC

MD5

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+b1dc3a24f10e27c9d4b858ed660685b5 *DESCRIPTION
+15ae49177bef8caae852efb3cacc2687 *NAMESPACE
+d470f53ffb063dfad64cf69df1b480da *NEWS.md
+be94a383285ccfa41fb39421d98bdcb2 *R/RcppExports.R
+1384d637ac4ca5c16f415f731a2387fa *R/libstable4u-pkg.r
+027e8f59840a17710f16fb178a4b4430 *demo/00Index
+9c9c187b3fc20b9825b33dccf65d8a83 *demo/libstable4u_demo.R
+2dea68e1b3905bfbe92842394f79f9a0 *inst/CITATION
+dafffffef0bc305f9747cd58b3e686e9 *man/libstable4u.Rd
+59ebda57644630ef107df8d5f9866059 *man/stable_fit.Rd
+c20aead0e493daa2191ce340fb884f8a *man/stable_pdf_and_cdf.Rd
+e9750952f96753e0802abe5c447d4187 *man/stable_q.Rd
+68773d6596ae684ba17fca075ed92ae4 *man/stable_rnd.Rd
+ea23ea2a1d8638bc8e095aaea8bbd943 *src/Makevars
+609a1b18d56e547625d73675f5d8125f *src/RcppExports.cpp
+c0c5b95f8dac7376b29802b624d63146 *src/mcculloch.c
+a820b5f0f12af98e50aa79db4243b793 *src/mcculloch.h
+a7c8080b609d51a8c3f33fad4bb89d83 *src/methods.c
+6ae1fe5df27f307dabe7ba13ea178484 *src/methods.h
+48aaa55aec84d21ec40fe67722ee69f7 *src/stable.h
+c6920925bca9c20a13885051cd5bd62f *src/stable_R.cpp
+0b4d755d69d9daa1eef48dbc74ad890a *src/stable_cdf.c
+8c19b32ffd56269c34db070b51ad8251 *src/stable_common.c
+0942e6eeba0e8464d1cae1fb39fdb1ae *src/stable_dist.c
+fc9c67363a585715bf45eac31b3d4ef9 *src/stable_fit.c
+e453f4516766b7287609c052389ca7ba *src/stable_fit.h
+fabe616c7f30b3e769e7402b5d2aa583 *src/stable_integration.c
+f60ae7b92d5965fb417ec9168177b6a4 *src/stable_integration.h
+602c7881db70969222a2dced8c2ae39b *src/stable_koutrouvelis.c
+1aeee1acd665933ad8623fa8c0707858 *src/stable_pdf.c
+316f8181470ce89d304a2103cfa7fdab *src/stable_q.c
+0b0a55f0408b7ff5cd94755cf5c8a844 *src/stable_rnd.c
+0e8f7d1a818cd996497e07ff938b27ea *tests/testthat.R
+591b8c85fbaa87a2f9760ae14f0e559f *tests/testthat/test-stable-df.R

NAMESPACE

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+# Generated by roxygen2: do not edit by hand
+
+export(stable_cdf)
+export(stable_fit_init)
+export(stable_fit_koutrouvelis)
+export(stable_fit_mle)
+export(stable_fit_mle2d)
+export(stable_pdf)
+export(stable_q)
+export(stable_rnd)
+importFrom(Rcpp,evalCpp)
+importFrom(Rcpp,sourceCpp)
+useDynLib(libstable4u, .registration=TRUE)

NEWS.md

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+------------------------------------------------------------------------------
+version 1.0.2
+------------------------------------------------------------------------------
+
+  * Posted as copy of (recently archived) `libstableR v1.0.2` + minor edits for CRAN acceptance

R/RcppExports.R

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+# Generated by using Rcpp::compileAttributes() -> do not edit by hand
+# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
+
+#' @md
+#' @name stable_pdf_and_cdf
+#' @aliases stable_cdf stable_pdf
+#' @title PDF and CDF of a skew stable distribution.
+#' @description Evaluate the PDF or the CDF of the skew stable distribution with parameters
+#' pars = c(alpha, beta, sigma, mu) at the points given in x.\cr\cr
+#' _parametrization_ argument specifies the parametrization used for the distribution
+#' as described by JP Nolan (1997). The default value is _parametrization_ = 0.\cr\cr
+#' _tol_ sets the relative error tolerance (precision) to _tol_. The default value is tol = 1e-12.
+#' @param x Vector of points where the pdf will be evaluated.
+#' @param pars Vector with an initial estimation of the parameters. `pars_init = c(alpha, beta, sigma, mu)`, where
+#' * alpha: shape / stability parameter, with 0 < alpha <= 2.
+#' * beta: skewness parameter, with -1 <= beta <= 1.
+#' * sigma: scale parameter, with 0 < sigma.
+#' * mu: location parameter, with mu real.
+#' @param parametrization Parametrization used for the skew stable distribution, as defined by JP Nolan (1997). By default, parametrization = 0.
+#' @param tol Relative error tolerance (precission) of the calculated values. By default, tol = 1e-12.
+#' @return A numeric vector.
+#' @author Javier Royuela del Val, Federico Simmross Wattenberg and Carlos Alberola López\cr\cr
+#'         Maintainer: Javier Royuela del Val <jroyval@@lpi.tel.uva.es>
+#' @references Nolan JP (1997). Numerical Calculation of Stable Densities and Distribution Functions. Stochastic Models, 13(4) 759-774.
+#' @keywords distribution
+#' @examples
+#' pars <- c(1.5, 0.9, 1, 0)
+#' x <- seq(-5, 10, 0.001)
+#'
+#' pdf <- stable_pdf(x, pars)
+#' cdf <- stable_cdf(x, pars)
+#'
+#' plot(x, pdf, type = "l")
+#' @export
+stable_pdf <- function(x, pars, parametrization = 0L, tol = 1e-12) {
+    .Call(`_libstable4u_stable_pdf`, x, pars, parametrization, tol)
+}
+
+#' @export
+stable_cdf <- function(x, pars, parametrization = 0L, tol = 1e-12) {
+    .Call(`_libstable4u_stable_cdf`, x, pars, parametrization, tol)
+}
+
+#' @md
+#' @title Quantile function of skew stable distributions
+#' @description Evaluate the quantile function (CDF^-1) of the skew stable distribution
+#' with parameters pars = c(alpha, beta, sigma, mu) at the points given in p.\cr\cr
+#' _parametrization_ argument specifies the parametrization used for the distribution
+#' as described by JP Nolan (1997). The default value is _parametrization_ = 0.\cr\cr
+#' _tol_ sets the relative error tolerance (precission) to _tol_. The default value is tol = 1e-12.
+#' @param p Vector of points where the quantile function will be evaluated, with  0 < p\[i] < 1.0
+#' @param pars Vector with an initial estimation of the parameters. `pars_init = c(alpha, beta, sigma, mu)`, where
+#' * alpha: shape / stability parameter, with 0 < alpha <= 2.
+#' * beta: skewness parameter, with -1 <= beta <= 1.
+#' * sigma: scale parameter, with 0 < sigma.
+#' * mu: location parameter, with mu real.
+#' @param parametrization Parametrization used for the skew stable distribution, as defined by JP Nolan (1997). By default, parametrization = 0.
+#' @param tol Relative error tolerance (precission) of the calculated values. By default, tol = 1e-12.
+#' @return A numeric vector.
+#' @author Javier Royuela del Val, Federico Simmross Wattenberg and Carlos Alberola López\cr\cr
+#'         Maintainer: Javier Royuela del Val <jroyval@@lpi.tel.uva.es>
+#' @keywords distribution
+#' @export
+stable_q <- function(p, pars, parametrization = 0L, tol = 1e-12) {
+    .Call(`_libstable4u_stable_q`, p, pars, parametrization, tol)
+}
+
+#' @md
+#' @title Skew stable distribution random sample generation.
+#' @description `stable_rnd(N, pars)` generates N random samples of a skew stable distribuiton
+#' with parameters pars = c(alpha, beta, sigma, mu) using the Chambers, Mallows,
+#' and Stuck (1976) method.\cr\cr
+#' @param N Number of values to generate.
+#' @param pars Vector with an initial estimation of the parameters. `pars_init = c(alpha, beta, sigma, mu)`, where
+#' * alpha: shape / stability parameter, with 0 < alpha <= 2.
+#' * beta: skewness parameter, with -1 <= beta <= 1.
+#' * sigma: scale parameter, with 0 < sigma.
+#' * mu: location parameter, with mu real.
+#' @param parametrization Parametrization used for the skew stable distribution, as defined by JP Nolan (1997). By default, parametrization = 0.
+#' @references Chambers JM, Mallows CL, Stuck BW (1976). A Method for Simulating Stable Random Variables. Journal of the American Statistical Association, 71(354), 340-344. doi:10.1080/01621459.1976.10480344.
+#' @return A numeric vector.
+#' @author Javier Royuela del Val, Federico Simmross Wattenberg and Carlos Alberola López\cr\cr
+#'         Maintainer: Javier Royuela del Val <jroyval@@lpi.tel.uva.es>
+#' @keywords distribution
+#' @examples
+#' N <- 1000
+#' pars <- c(1.25, 0.95, 1.0, 0.0)
+#' rnd <- stable_rnd(N, pars)
+#'
+#' hist(rnd)
+#' @export
+stable_rnd <- function(N, pars, parametrization = 0L) {
+    .Call(`_libstable4u_stable_rnd`, N, pars, parametrization)
+}
+
+#' @md
+#' @title Methods for parameter estimation of skew stable distributions.
+#' @name stable_fit
+#' @aliases stable_fit_init stable_fit_koutrouvelis stable_fit_mle stable_fit_mle2d
+#' @description A set of functions are provided that perform the parameter estimation of skew stable distributions with different methods.
+#' @details
+#' * `stable_fit_init()` uses McCulloch's method of quantiles \[3]. This is usually a good initialization for the rest of the methods.
+#' * `stable_fit_koutrouvelis()` implements Koutrouvellis' method based on the characteristic function \[4].
+#' * `stable_fit_mle()` implements a Maximum likelihood estimation.
+#' * `stable_fit_mle2()` implements a modified maximum likelihood estimation as described in \[1].
+#' @param rnd Random sample
+#' @param parametrization Parametrization used for the skew stable distribution, as defined by JP Nolan (1997). By default, parametrization = 0.
+#' @return A numeric vector.
+#' @references
+#' * \[1] Royuela-del-Val J, Simmross-Wattenberg F, Alberola López C (2017). libstable: Fast, Parallel and High-Precision Computation of alpha-stable Distributions in R, C/C++ and MATLAB. Journal of Statistical Software, 78(1), 1-25. doi:10.18637/jss.v078.i01
+#' * \[2] Chambers JM, Mallows CL, Stuck BW (1976). A Method for Simulating Stable Random Variables. Journal of the American Statistical Association, 71(354), 340-344. doi:10.1080/01621459.1976.10480344.
+#' * \[3] McCulloch JH (1986). Simple Consistent Estimators of Stable Distribution Parameters. Communications in Statistics - Simulation and Computation, 15(4), 1109-1136. doi:10.1080/03610918608812563.
+#' * \[4] Koutrouvelis IA (1981). An Iterative Procedure for the Estimation of the Parameters of Stable Laws. Communications in Statistics - Simulation and Computation, 10(1), 17-28. doi:10.1080/03610918108812189.
+#' * \[5] Nolan JP (1997). Numerical Calculation of Stable Densities and Distribution Functions. Stochastic Models, 13(4) 759-774. doi:10.1080/15326349708807450.
+#' @keywords distribution
+#' @author Javier Royuela del Val, Federico Simmross Wattenberg and Carlos Alberola López\cr\cr
+#'         Maintainer: Javier Royuela del Val <jroyval@@lpi.tel.uva.es>
+#' @examples
+#' # Set alpha, beta, sigma and mu stable parameters in a vector
+#' pars <- c(1.5, 0.9, 1, 0)
+#'
+#' # Generate random values
+#' set.seed(1)
+#' rnd <- stable_rnd(100, pars)
+#' head(rnd)
+#'
+#' # Estimate the parameters of the skew stable distribution given
+#' # the generated sample:
+#'
+#' # Using the McCulloch's estimator:
+#' pars_init <- stable_fit_init(rnd)
+#'
+#' # Using the Koutrouvelis' estimator, with McCulloch estimation
+#' # as a starting point:
+#' pars_est_K <- stable_fit_koutrouvelis(rnd, pars_init)
+#'
+#' # Using maximum likelihood estimator:
+#' pars_est_ML <- stable_fit_mle(rnd, pars_est_K)
+#'
+#' # Using modified maximum likelihood estimator (see [1]):
+#' pars_est_ML2 <- stable_fit_mle2d(rnd, pars_est_K)
+#' @export
+stable_fit_init <- function(rnd, parametrization = 0L) {
+    .Call(`_libstable4u_stable_fit_init`, rnd, parametrization)
+}
+
+#' @md
+#' @rdname stable_fit
+#' @param pars_init Vector with an initial estimation of the parameters. `pars_init = c(alpha, beta, sigma, mu)`, where
+#' * alpha: shape / stability parameter, with 0 < alpha <= 2.
+#' * beta: skewness parameter, with -1 <= beta <= 1.
+#' * sigma: scale parameter, with 0 < sigma.
+#' * mu: location parameter, with mu real.
+#' @export
+stable_fit_koutrouvelis <- function(rnd, pars_init = as.numeric( c()), parametrization = 0L) {
+    .Call(`_libstable4u_stable_fit_koutrouvelis`, rnd, pars_init, parametrization)
+}
+
+#' @export
+stable_fit_mle <- function(rnd, pars_init = as.numeric( c()), parametrization = 0L) {
+    .Call(`_libstable4u_stable_fit_mle`, rnd, pars_init, parametrization)
+}
+
+#' @export
+stable_fit_mle2d <- function(rnd, pars_init = as.numeric( c()), parametrization = 0L) {
+    .Call(`_libstable4u_stable_fit_mle2d`, rnd, pars_init, parametrization)
+}
+

R/libstable4u-pkg.r

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+#' libstable4u: Fast and accurate evaluation, random number generation
+#' and parameter estimation of skew stable distributions.
+#'
+#' libstable4u provides functions to work with skew stable distributions
+#' in a fast and accurate way \[1]. It performs:
+#'
+#' * Fast and accurate evaluation of the probability density function (PDF) and cumulative density function (CDF).
+#' * Fast and accurate evaluation of the quantile function (CDF^{-1}).
+#' * Random numbers generation \[2].
+#' * Skew stable parameter estimation with:
+#'     * McCulloch's method of quantiles \[3].
+#'     * Koutrouvellis' method based on the characteristic function \[4].
+#'     * Maximum likelihood estimation.
+#'     * Modified maximum likelihood estimation as described in \[1].
+#' *The evaluation of the PDF and CDF is based on the formulas provided by John P Nolan in \[5].
+#'
+#' @md
+#' @author Javier Royuela del Val, Federico Simmross Wattenberg and Carlos Alberola López;\cr\cr
+#'         Maintainer: Javier Royuela del Val <jroyval@@lpi.tel.uva.es>
+#' @references
+#' * \[1] Royuela-del-Val J, Simmross-Wattenberg F, Alberola López C (2017). libstable: Fast, Parallel and High-Precision Computation of alpha-stable Distributions in R, C/C++ and MATLAB. Journal of Statistical Software, 78(1), 1-25. doi:10.18637/jss.v078.i01
+#' * \[2] Chambers JM, Mallows CL, Stuck BW (1976). A Method for Simulating Stable Random Variables. Journal of the American Statistical Association, 71(354), 340-344. doi:10.1080/01621459.1976.10480344
+#' * \[3] McCulloch JH (1986). Simple Consistent Estimators of Stable Distribution Parameters. Communications in Statistics - Simulation and Computation, 15(4), 1109-1136. doi:10.1080/03610918608812563
+#' * \[4] Koutrouvelis IA (1981). An Iterative Procedure for the Estimation of the Parameters of Stable Laws. Communications in Statistics - Simulation and Computation, 10(1), 17-28. doi:10.1080/03610918108812189
+#' * \[5] Nolan JP (1997). Numerical Calculation of Stable Densities and Distribution Functions. Stochastic Models, 13(4), 759-774. doi:10.1080/15326349708807450
+#' @name libstable4u
+#' @docType package
+#' @keywords package
+#' @useDynLib libstable4u, .registration=TRUE
+#' @importFrom Rcpp sourceCpp evalCpp
+#' @examples
+#' # Set alpha, beta, sigma and mu stable parameters in a vector
+#' pars <- c(1.5, 0.9, 1, 0)
+#'
+#' # Generate an abscissas axis and probabilities vector
+#' x <- seq(-5, 10, 0.05)
+#' p <- seq(0.01, 0.99, 0.01)
+#'
+#' # Calculate pdf, cdf and quantiles
+#' pdf <- stable_pdf(x, pars)
+#' cdf <- stable_cdf(x, pars)
+#' xq  <- stable_q(p, pars)
+#'
+#' # Generate random values
+#' set.seed(1)
+#' rnd <- stable_rnd(100, pars)
+#' head(rnd)
+#'
+#' # Estimate the parameters of the skew stable distribution given
+#' # the generated sample:
+#'
+#' # Using the McCulloch's estimator:
+#' pars_init <- stable_fit_init(rnd)
+#'
+#' # Using the Koutrouvelis' estimator, with McCulloch estimation
+#' # as a starting point:
+#' pars_est_K <- stable_fit_koutrouvelis(rnd, pars_init)
+#'
+#' # Using maximum likelihood estimator:
+#' pars_est_ML <- stable_fit_mle(rnd, pars_est_K)
+#'
+#' # Using modified maximum likelihood estimator (see [1]):
+#' pars_est_ML2 <- stable_fit_mle2d(rnd, pars_est_K)
+NULL

demo/00Index

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+libstable4u_demo    libstable4u package demo