Package: gnFit 0.2.0
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.
Authors:
gnFit_0.2.0.tar.gz
gnFit_0.2.0.zip(r-4.7)gnFit_0.2.0.zip(r-4.6)gnFit_0.2.0.zip(r-4.5)
gnFit_0.2.0.tgz(r-4.6-any)gnFit_0.2.0.tgz(r-4.5-any)
gnFit_0.2.0.tar.gz(r-4.7-any)gnFit_0.2.0.tar.gz(r-4.6-any)
gnFit_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
gnFit/json (API)
| # Install 'gnFit' in R: |
| install.packages('gnFit', repos = c('https://asaeb1480.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:27ee29d79d. Checks:9 OK. Indexed: yes.
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Goodness of Fit Test for Continuous Distribution Functions | gnfit |
| Risk Factors | rskFac |
