ppcc: Probability Plot Correlation Coefficient Test

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


Please use the canonical form https://CRAN.R-project.org/package=ppcc to link to this page.