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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1 |
rolling source/ R- | energyGOF_0.1.tar.gz |
35.2 KiB |
0.1 |
latest source/ R- | energyGOF_0.1.tar.gz |
35.2 KiB |
0.1 |
2026-04-09 windows/windows R-4.5 | energyGOF_0.1.zip |
185.0 KiB |