Importance Sampling to Accelerate the Convergence of Quasi-Monte Carlo

Wolfgang Hörmann, Josef Leydold

Publikation: Working/Discussion PaperWU Working Paper

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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)
HerausgeberDepartment of Statistics and Mathematics, WU Vienna University of Economics and Business
PublikationsstatusVeröffentlicht - 2007


ReiheResearch Report Series / Department of Statistics and Mathematics

WU Working Paper Reihe

  • Research Report Series / Department of Statistics and Mathematics