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-devel-UCRT: 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-release (x86_64): vsgoftest_1.0-1.tgz, r-oldrel: vsgoftest_1.0-1.tgz
Old sources: vsgoftest archive

Linking:

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