Importance sampling is a well known variance reduction technique for Monte Carlo simulation. For quasi-Monte Carlo integration with low discrepancy sequences it was neglected in the literature although it is easy to see that it can reduce the variation of the integrand for many important integration problems. For lattice rules importance sampling is of highest importance as it can be used to obtain a smooth periodic integrand. Thus the convergence of the integration procedure is accelerated. This can clearly speed up QMC algorithms for integration problems up to dimensions 10 to 12. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics
Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:epub-wu-01_b88 |
Date | January 2007 |
Creators | Hörmann, Wolfgang, Leydold, Josef |
Publisher | Department of Statistics and Mathematics, WU Vienna University of Economics and Business |
Source Sets | Wirtschaftsuniversität Wien |
Language | English |
Detected Language | English |
Type | Paper, NonPeerReviewed |
Format | application/pdf |
Relation | http://epub.wu.ac.at/284/ |
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