摘要: SUMMARY This paper proposes a post-simulation improvement for two common Monte Carlo methods, the Accept-Reject and Metropolis algorithms. The is based on Rao-Blackwellisation method that integrates over uniform random variables involved in algorithms, thus post-processes standard estimators. We show how Rao-Blackwellised versions of these algorithms can be implemented and, through examples, illustrate variance brought by new procedures. also compare improved version algorithm with ordinary importance sampling procedures independent general set-ups.
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