A class of proper priors for Bayesian simultaneous prediction of independent Poisson observables
Simultaneous prediction and parameter inference for the independent Poisson observables model are considered. A class of proper prior distributions for Poisson means is introduced. Bayesian predictive densities and estimators based on priors in the introduced class dominate the Bayesian predictive density and estimator based on the Jeffreys prior under Kullback-Leibler loss.
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Volume (Year): 97 (2006)
Issue (Month): 8 (September)
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