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.

gnFit URL: https://github.com/cran/gnFit

*** Version 0.2.0 (Jun, 2018)

• Added the function of "rskFac" to calculate the Value at Risk and Conditional Value at Risk

*** Version 0.1.0 (November 5, 2017)

• First commit