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 (may not be active yet)
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: not available, 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:

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