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On a Posterior Predictive Density Sample Size Criterion
Authors:THEODOROS NICOLERIS   STEPHEN G. WALKER
Affiliation:Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean; Institute of Mathematics, Statistics and Actuarial Science, University of Kent
Abstract:Abstract.  Let Ω be a space of densities with respect to some σ -finite measure μ and let Π be a prior distribution having support Ω with respect to some suitable topology. Conditional on f , let X n  = ( X 1 ,…, X n ) be an independent and identically distributed sample of size n from f . This paper introduces a Bayesian non-parametric criterion for sample size determination which is based on the integrated squared distance between posterior predictive densities. An expression for the sample size is obtained when the prior is a Dirichlet mixture of normal densities.
Keywords:integrated squared distance    martingale    mixtures of Dirichlet processes    posterior predictive density    sample size
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