Importance Sampling to Accelerate the Convergence of Quasi-Monte Carlo

Hörmann, Wolfgang and Leydold, Josef (2007) Importance Sampling to Accelerate the Convergence of Quasi-Monte Carlo. Research Report Series / Department of Statistics and Mathematics, 49. Department of Statistics and Mathematics, WU Vienna University of Economics and Business, Vienna.

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Abstract

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)

Item Type: Paper
Keywords: Monte Carlo integration / lattice rules / low discrepancy sequence / highly uniform point sets / importance sampling
Classification Codes: MSC_65C05
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 13 Feb 2007 09:45
Last Modified: 22 Oct 2019 00:41
URI: https://epub.wu.ac.at/id/eprint/284

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