Different approaches for selecting the threshold in generalized Pareto distributions. Most of them are based on minimizing the AMSEcriterion or at least by reducing the bias of the assumed GPDmodel. Others are heuristically motivated by searching for stable sample paths, i.e. a nearly constant region of the tail index estimator with respect to k, which is the number of data in the tail. The third class is motivated by graphical inspection. In addition to the very helpful eva package which includes many goodness of fit tests for the generalized Pareto distribution, the sequential testing procedure provided in Thompson et al. (2009)
Package details 


Author  Johannes Ossberger 
Date of publication  20170122 17:02:24 
Maintainer  Johannes Ossberger <[email protected]> 
License  GPL2 
Version  1.0 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.