Goodness of Fit Test for Continuous Distribution Functions
Overview
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.
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Ali Saeb <ali.saeb@gmail.com>’
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Authors@R: person(given = "Ali",
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as necessary.- NOTE11 OK, 2 NOTENow
- NOTE9 OK, 5 NOTE2026-03-10
Documentation
- Help pages
- 2
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- 100%2 run in a plain check
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- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- 0.2.0Latest
- RR 3.5.0 released · 2018-04-23
- 0.1.02017-11-05
- RR 3.4.0 released · 2017-04-21
Package metadata
- First published
- 2017-11-05
- Total releases
- 2 / 9 yrs
- License
- GPL
- Download size
- 5.9 KB
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