  For extreme value estimation we propose to use a model with a Dirichlet
process mixture of gamma densities in the center and generalized Pareto
densities for the tails. Due to the randomness in the center and a heavy tailed
density in the tails density estimation and posterior inference for high
quantiles are possible. The approach can be used in a "default" manner on the
positive reals because it works when prior information is unavailable. The
proposed model can be easy to implement and a sensitivity analysis is provided.
We applied the proposed model for simulated and real data sets.
