Goodness-of-Fit Tests for Univariate Data via Energy
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 22includes a package overview page
- Examples that run
- 100%20 run in a plain check
- Exported functions with examples
- 95%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 5%
Downloads
Repository
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Checks run against github.com/jthaman/energygof on 2026-10-22.
No development-tooling practices detected in the upstream repository.
Dependencies
Installing energyGOF adds 6 packages (5 with compiled code, 5.3 MB of source tarballs). Heaviest: fitdistrplus 2.4 MB, Rcpp 1.8 MB, rlang 766 KB.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- 0.1Latest2025-12-01 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-12-01
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 3) OSI
- Download size
- 35 KB
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