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Calculates the Probability Plot Correlation Coefficient (PPCC) between a continuous variable X and a specified distribution. The corresponding composite hypothesis test that was first introduced by Filliben (1975) <doi:10.1080/00401706.1975.10489279> can be performed to test whether the sample X is element of either the Normal, log-Normal, Exponential, Uniform, Cauchy, Logistic, Generalized Logistic, Gumbel (GEVI), Weibull, Generalized Extreme Value, Pearson III (Gamma 2), Mielke's Kappa, Rayleigh or Generalized Logistic Distribution. The PPCC test is performed with a fast Monte-Carlo simulation.
| Version: | 1.2 |
| Depends: | R (≥ 3.0.0) |
| Suggests: | VGAM (≥ 1.0), nortest (≥ 1.0) |
| Published: | 2020-02-01 |
| DOI: | 10.32614/CRAN.package.ppcc |
| Author: | Thorsten Pohlert |
| Maintainer: | Thorsten Pohlert <thorsten.pohlert at gmx.de> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | ppcc results |
| Reference manual: | ppcc.pdf |
| Package source: | ppcc_1.2.tar.gz |
| Windows binaries: | r-devel: ppcc_1.2.zip, r-release: ppcc_1.2.zip, r-oldrel: ppcc_1.2.zip |
| macOS binaries: | r-release (arm64): ppcc_1.2.tgz, r-oldrel (arm64): ppcc_1.2.tgz, r-release (x86_64): ppcc_1.2.tgz, r-oldrel (x86_64): ppcc_1.2.tgz |
| Old sources: | ppcc archive |
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