gPd.fit {gPdtest} | R Documentation |
This function fits a generalized Pareto distribution (gPd) to a data set using either the asymptotic maximum likelihood method (amle) or the combined method proposed by Villasenor-Alva and Gonzalez-Estrada (2009).
gPd.fit(x,method)
x |
numeric data vector containing a random sample from a distribution function with support on the positive real numbers. |
method |
a character string giving the name of the parameter estimation method to be used. There are two available methods: "combined" and "amle" . Use "combined" for fitting a gPd with shape parameter <0. Use "amle"
for fitting a gPd with shape parameter >= 0. |
The distribution function of the gPd is given in the details section of the function gPd.test
.
The parameter estimates.
Elizabeth Gonzalez Estrada, Jose A. Villasenor Alva
Villasenor-Alva, J.A. and Gonzalez-Estrada, E. (2009). A bootstrap goodness of fit test for the generalized Pareto distribution. Computational Statistics and Data Analysis,53,11,3835-3841.
gPd.test
for testing the gPd hypothesis, rgPd
for generating gPd random numbers.
x <- rgPd(20,shape = 1) ## Random sample of size 20 gPd.fit(x,"amle") ## Fitting a gPd to x using the "amle" method