Efficient Monte Carlo simulation via the generalized splitting method

Botev, Zdravko I. and Kroese, Dirk P. (2012) Efficient Monte Carlo simulation via the generalized splitting method. Statistics and Computing, 22 1: 171-16. doi:10.1007/s11222-010-9201-4


Author Botev, Zdravko I.
Kroese, Dirk P.
Title Efficient Monte Carlo simulation via the generalized splitting method
Journal name Statistics and Computing   Check publisher's open access policy
ISSN 0960-3174
1573-1375
Publication date 2012-01-01
Year available 2010
Sub-type Article (original research)
DOI 10.1007/s11222-010-9201-4
Volume 22
Issue 1
Start page 171
End page 16
Total pages 16
Place of publication Secaucus, NJ, United States
Publisher Springer New York
Collection year 2011
Language eng
Abstract We describe a new Monte Carlo algorithm for the consistent and unbiased estimation of multidimensional integrals and the efficient sampling from multidimensional densities. The algorithm is inspired by the classical splitting method and can be applied to general static simulation models. We provide examples from rare-event probability estimation, counting, and sampling, demonstrating that the proposed method can outperform existing Markov chain sampling methods in terms of convergence speed and accuracy.
Keyword Boolean Satisfiability problem
Combinatorial counting
Convergence diagnostic
Fixed effort
Fixed splitting
Importance sampling
Level-crossing
MCMC
Rare-event probability estimation
RESTART
Sequential Monte Carlo
Splitting method
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Available online 16 September 2010.

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
Official 2011 Collection
 
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Citation counts: TR Web of Science Citation Count  Cited 33 times in Thomson Reuters Web of Science Article | Citations
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Created: Tue, 15 Mar 2011, 20:36:36 EST by Prof Dirk P. Kroese on behalf of School of Mathematics & Physics