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energyGOF: Goodness-of-Fit Tests for Univariate Data via Energy

Conduct one- and two-sample goodness-of-fit tests for univariate data. In the one-sample case, normal, uniform, exponential, Bernoulli, binomial, geometric, beta, Poisson, lognormal, Laplace, asymmetric Laplace, inverse Gaussian, half-normal, chi-squared, gamma, F, Weibull, Cauchy, and Pareto distributions are supported. egof.test() can also test goodness-of-fit to any distribution with a continuous distribution function. A subset of the available distributions can be tested for the composite goodness-of-fit hypothesis, that is, one can test for distribution fit with unknown parameters. P-values are calculated via parametric bootstrap.

Version:0.1
Imports:energy,gsl,boot,fitdistrplus,statmod
Suggests:testthat (≥ 3.0.0)
Published:2025-12-01
DOI:10.32614/CRAN.package.energyGOF
Author:John Haman [aut, cre]
Maintainer:John Haman <mail at johnhaman.org>
License:GPL (≥ 3)
URL:https://github.com/jthaman/energyGOF
NeedsCompilation:no
Materials:README
CRAN checks:energyGOF results

Documentation:

Reference manual:energyGOF.html ,energyGOF.pdf

Downloads:

Package source: energyGOF_0.1.tar.gz
Windows binaries: r-devel:energyGOF_0.1.zip, r-release:energyGOF_0.1.zip, r-oldrel:energyGOF_0.1.zip
macOS binaries: r-release (arm64):energyGOF_0.1.tgz, r-oldrel (arm64):energyGOF_0.1.tgz, r-release (x86_64):energyGOF_0.1.tgz, r-oldrel (x86_64):energyGOF_0.1.tgz

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=energyGOFto link to this page.


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