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: | 1.1 |
Depends: | R (≥ 3.0.0) |
Suggests: | VGAM (≥ 1.0), nortest (≥ 1.0) |
Published: | 2018-12-03 |
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_1.1.tar.gz |
Windows binaries: | r-devel: ppcc_1.1.zip, r-release: ppcc_1.1.zip, r-oldrel: ppcc_1.1.zip |
OS X binaries: | r-release: ppcc_1.1.tgz, r-oldrel: ppcc_1.1.tgz |
Old sources: | ppcc archive |
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