An algorithm for nonparametric Bayesian estimation of a Poisson intensity
A nonparametric Bayesian algorithm is described for the estimation of intensity of a non-homogeneous Poisson process. The unknown intensity is approximated by a picewise constant function. The number of jumps as well as jump points and levels of the estimator are selected by an iterative Monte-Carlo algorithm based on the ratios of prior and posterior densities. Results of simulations are presented.
scientific article; zbMATH DE number 1129909