A Review on the Exact Monte Carlo Simulation

Hongsheng Dai

A chapter in Bayesian Inference on Complicated Data from IntechOpen

Abstract: Perfect Monte Carlo sampling refers to sampling random realizations exactly from the target distributions (without any statistical error). Although many different methods have been developed and various applications have been implemented in the area of perfect Monte Carlo sampling, it is mostly referred by researchers to coupling from the past (CFTP) which can correct the statistical errors for the Monte Carlo samples generated by Markov chain Monte Carlo (MCMC) algorithms. This paper provides a brief review on the recent developments and applications in CFTP and other perfect Monte Carlo sampling methods.

Keywords: coupling from the past; diffusion; Monte Carlo; perfect sampling (search for similar items in EconPapers)
JEL-codes: C60 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:199896

DOI: 10.5772/intechopen.88619

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