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

Documentation:

Reference manual:

ppcc.pdf

Downloads:

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

Linking:

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