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 |
| Author: |
Thorsten Pohlert |
| Maintainer: |
Thorsten Pohlert <thorsten.pohlert at gmx.de> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| Materials: |
NEWS |
| CRAN checks: |
ppcc results |
Documentation:
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