vsgoftest: Goodness-of-Fit Tests Based on Kullback-Leibler Divergence

An implementation of Vasicek and Song goodness-of-fit tests. Several functions are provided to estimate differential Shannon entropy, i.e., estimate Shannon entropy of real random variables with density, and test the goodness-of-fit of some family of distributions, including uniform, Gaussian, log-normal, exponential, gamma, Weibull, Pareto, Fisher, Laplace and beta distributions; see Lequesne and Regnault (2020) <doi:10.18637/jss.v096.c01>.

Version:	1.0-1
Depends:	stats, fitdistrplus
Imports:	Rcpp (≥ 0.12.1)
LinkingTo:	Rcpp
Suggests:	knitr
Published:	2020-12-17
Author:	Justine Lequesne [aut], Philippe Regnault [aut, cre]
Maintainer:	Philippe Regnault <philipperegnault at hotmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
Citation:	vsgoftest citation info
CRAN checks:	vsgoftest results

Documentation:

Reference manual:	vsgoftest.pdf
Vignettes:	Tutorial

Downloads:

Package source:	vsgoftest_1.0-1.tar.gz
Windows binaries:	r-devel: vsgoftest_1.0-1.zip, r-release: vsgoftest_1.0-1.zip, r-oldrel: vsgoftest_1.0-1.zip
macOS binaries:	r-release (arm64): vsgoftest_1.0-1.tgz, r-oldrel (arm64): vsgoftest_1.0-1.tgz, r-release (x86_64): vsgoftest_1.0-1.tgz, r-oldrel (x86_64): vsgoftest_1.0-1.tgz
Old sources:	vsgoftest archive

Linking:

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