Calculates the Probability Plot Correlation Coefficient (PPCC) between a continuous variable X and a specified distribution. The corresponding composite hypothesis test can be done 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: | 1.0 |
| Depends: | R (≥ 3.0.0) |
| Suggests: | VGAM (≥ 1.0), nortest (≥ 1.0) |
| Published: | 2017-06-28 |
| Author: | Thorsten Pohlert |
| Maintainer: | Thorsten Pohlert <thorsten.pohlert at gmx.de> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | ppcc results |
| Reference manual: | ppcc.pdf |
| Package source: | ppcc_1.0.tar.gz |
| Windows binaries: | r-devel: ppcc_1.0.zip, r-release: ppcc_1.0.zip, r-oldrel: ppcc_1.0.zip |
| OS X El Capitan binaries: | r-release: ppcc_1.0.tgz |
| OS X Mavericks binaries: | r-oldrel: ppcc_1.0.tgz |
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