gnFit: Goodness of Fit Test for Continuous Distribution Functions

Computes the test statistic and p-value of the Cramer-von Mises and Anderson-Darling test for some continuous distribution functions proposed by Chen and Balakrishnan (1995) <http://asq.org/qic/display-item/index.html?item=11407>. In addition to our classic distribution functions here, we calculate the Goodness of Fit (GoF) test to dataset which follows the extreme value distribution function, without remembering the formula of distribution/density functions. Calculates the Value at Risk (VaR) and Average VaR are another important risk factors which are estimated by using well-known distribution functions. Pflug and Romisch (2007, ISBN: 9812707409) is a good reference to study the properties of risk measures.

Version: 0.2.0
Imports: ismev, rmutil
Published: 2018-06-07
Author: Ali Saeb
Maintainer: Ali Saeb <ali.saeb at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
Materials: README
CRAN checks: gnFit results

Downloads:

Reference manual: gnFit.pdf
Package source: gnFit_0.2.0.tar.gz
Windows binaries: r-devel: gnFit_0.2.0.zip, r-release: gnFit_0.2.0.zip, r-oldrel: gnFit_0.2.0.zip
OS X binaries: r-release: gnFit_0.2.0.tgz, r-oldrel: gnFit_0.2.0.tgz
Old sources: gnFit archive

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