ppcc

ppcc-package

<p>The function <code><a rd-options="" href="/link/ppccTest?package=ppcc&version=1.2" data-mini-rdoc="ppcc::ppccTest">ppccTest</a></code> performs
the Probability Plot Correlation Coefficient test
for various continuous distribution functions.</p>

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.

Thorsten Pohlert

Probability Plot Correlation Coefficient Test

ppcc-package function

<p>The function <code><a rd-options='' href='ppccTest'>ppccTest</a></code> performs
the Probability Plot Correlation Coefficient test
for various continuous distribution functions.</p>

ppcc-package: Goodness-of-Fit Tests using the Probability Plot Correlation Coefficient

Description

Arguments