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

Documentation:

Reference manual:

gnFit.pdf

Downloads:

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
macOS binaries:	r-release (arm64): gnFit_0.2.0.tgz, r-oldrel (arm64): gnFit_0.2.0.tgz, r-release (x86_64): gnFit_0.2.0.tgz, r-oldrel (x86_64): gnFit_0.2.0.tgz
Old sources:	gnFit archive

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