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gnFit
View on CRAN: Click
here
Download and install gnFit package within the R console
Install from CRAN:
install.packages("gnFit")
Install from Github:
library("remotes")
install_github("cran/gnFit")
Install by package version:
library("remotes")
install_version("gnFit", "0.2.0")
Attach the package and use:
library("gnFit")
Maintained by
Ali Saeb
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-11-05
Latest Update: 2018-06-07
Description:
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) . 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.
How to cite:
Ali Saeb (2017). gnFit: Goodness of Fit Test for Continuous Distribution Functions. R package version 0.2.0, https://cran.r-project.org/web/packages/gnFit. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.0 (2017-11-05 14:39)
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imports, suggests or enhances
Complete documentation for gnFit
Functions, R codes and Examples using
the gnFit R package
Some associated functions: gnfit . rskFac .
Some associated R codes: gnfit.R . rskFac.R . Full gnFit package functions and examples
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