A weighted discrepancy bound of quasi-Monte Carlo importance sampling

Josef Dick, Daniel Rudolf and Houying Zhu

Statistics & Probability Letters, 2019, vol. 149, issue C, 100-106

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.

Keywords: Importance sampling; Monte Carlo method; Quasi-Monte Carlo (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:149:y:2019:i:c:p:100-106

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DOI: 10.1016/j.spl.2019.01.014

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