Monte Carlo Integration in Bayesian Statistical Analysis

A review of Monte Carlo methods for approximating the high-dimensional integrals that arise in Bayesian statistical analysis. Emphasis is on the features of many Bayesian applications which make Monte Carlo methods especially appropriate, and on Monte Carlo variance-reduction techniques especially well suited to Bayesian applications. A generalized logistic regression example is used to illustrate the ideas, and high-precision formulas are given for implementing Bayesian Monte Carlo integration.

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