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 |

Reference manual: | gnFit.pdf |

Package source: | gnFit_0.2.0.tar.gz |

Windows binaries: | r-devel: gnFit_0.2.0.zip, r-devel-gcc8: 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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