On the convergence of quasi-random sampling/importance resampling

Bart Vandewoestyne and Ronald Cools

Mathematics and Computers in Simulation (MATCOM), 2010, vol. 81, issue 3, 490-505

Abstract: This article discusses the general problem of generating representative point sets from a distribution known up to a multiplicative constant. The sampling/importance resampling (SIR) algorithm is known to be useful in this context. Moreover, the quasi-random sampling/importance resampling (QSIR) scheme, based on quasi-Monte Carlo methods, is a more recent modification of the SIR algorithm and was empirically shown to have better convergence. By making use of quasi-Monte Carlo theory, we derive upper bounds for the error of the QSIR scheme.

Keywords: Sampling/importance resampling; Weighted bootstrap; Quasi-Monte Carlo methods; Bayesian inference (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:81:y:2010:i:3:p:490-505

DOI: 10.1016/j.matcom.2009.09.004

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