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 |
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