I am currently using the evd
package which fits a two-parameter GPD by maximum likelihood.
Since in small samples the MOM is superior to the ML estimation I'd like to give it a go. However, the POT package - which could do the job - is offline due to memory access errors.
There are many extreme value packages around. However I am ONLY interested in the two-parameter GPD given by
$G(y)= \begin{cases} 1-\left(1+ \frac{\xi y}{\beta} \right)^{-\frac{1}{\xi}} & \xi \neq 0 \\ 1-\exp\left(-\frac{y}{\beta}\right) & \xi=0 \end{cases}$
or alternatively
$g(y)= \begin{cases} \frac{1}{\beta} \left( 1+\frac{\xi y}{\beta} \right)^{-1-\frac{1}{\xi}} & \xi \neq 0 \\ \frac{1}{\beta} \exp\left(-\frac{y}{\beta} \right) & \xi=0 \end{cases}$
Is there any package that can fit such a distribution using a method of moments approach?