  In this paper we propose a model with a Dirichlet process mixture of gamma
densities in the bulk part below threshold and a generalized Pareto density in
the tail for extreme value estimation. The proposed model is simple and
flexible allowing us posterior density estimation and posterior inference for
high quantiles. The model works well even for small sample sizes and in the
absence of prior information. We evaluate the performance of the proposed model
through a simulation study. Finally, the proposed model is applied to a real
environmental data.
