A weighted discrepancy bound of quasi-Monte Carlo importance sampling

Josef Dick, Daniel Rudolf, Houying Zhu

Research output: Contribution to journalArticlepeer-review

Abstract

Importance sampling Monte-Carlo methods are widely used for the approximation of expectations with respect to partially known probability measures. In this paper we study a deterministic version of such an estimator based on quasi-Monte Carlo. We obtain an explicit error bound in terms of the star-discrepancy for this method.

Original languageEnglish
Pages (from-to)100-106
Number of pages7
JournalStatistics and Probability Letters
Volume149
DOIs
Publication statusPublished - Jun 2019
Externally publishedYes

Keywords

  • Importance sampling
  • Monte Carlo method
  • Quasi-Monte Carlo

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