BIRS Workshop Lecture Videos

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BIRS Workshop Lecture Videos

Shrinkage priors for nonparametric Bayesian prediction of nonhomogeneous Poisson processes Komaki, Fumiyasu


A class of improper priors for nonhomogeneous Poisson intensity functions is proposed. The priors in the class have shrinkage properties. The nonparametric Bayesian predictive densities based on the shrinkage priors have reasonable properties, although improper priors have not been widely used for nonparametric Bayesian inference. In particular, the nonparametric Bayesian predictive densities are admissible under the Kullback-Leibler loss.

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