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energyGOF  

Goodness-of-Fit Tests for Univariate Data via Energy
View on CRAN: Click here


Download and install energyGOF package within the R console
Install from CRAN:
install.packages("energyGOF")

Install from Github:
library("remotes")
install_github("cran/energyGOF")

Install by package version:
library("remotes")
install_version("energyGOF", "0.1")



Attach the package and use:
library("energyGOF")
Maintained by
John Haman
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-12-01
Latest Update: 2025-12-01
Description:
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.
How to cite:
John Haman (2025). energyGOF: Goodness-of-Fit Tests for Univariate Data via Energy. R package version 0.1, https://cran.r-project.org/web/packages/energyGOF. Accessed 17 Jul. 2026.
Previous versions and publish date:
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Complete documentation for energyGOF
Functions, R codes and Examples using the energyGOF R package
Full energyGOF package functions and examples
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