Estimating the probability of obtaining nonfeasible parameter estimates of the generalized Pareto distribution

In this paper we consider the problem of estimating the parameters of the generalized Pareto distibution. Both the method of moments and probability-weighted moments do not guarantee that their respective estimates will be consistent with the observed data. We present simple programs to predict the probability of obtaining such nonfeasible estimates. Our estimation techniques are based on results from intensive simulations and the successful modelling of the lower tail of the distribution of the upper bound of the support. More simulations are performed to validate the new procedure.