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A review on the exact Monte Carlo simulation

Dai, Hongsheng (2019) 'A review on the exact Monte Carlo simulation.' In: Tang, Niansheng, (ed.) Bayesian Inference [Working Title]. IntechOpen.

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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.

Item Type: Book Section
Divisions: Faculty of Science and Health > Mathematical Sciences, Department of
Depositing User: Elements
Date Deposited: 24 Jan 2020 14:32
Last Modified: 24 Jan 2020 15:15

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