On the convergence of quasi-random sampling importance resampling

On the convergence of quasi-random sampling importance resampling

The Sampling/Importance Resampling (SIR) algorithm can be used for generating representative point sets from a distribution known up to a multiplicative constant. Moreover, the Quasi‐random Sampling Importance Resampling (QSIR) scheme, based on quasi‐Monte Carlo methods, is a recent modification of...

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Veröffentlicht in:Proceedings in applied mathematics and mechanics 2007-12, Vol.7 (1), p.1022401-1022402
Hauptverfasser: Cools, Ronald, Vandewoestyne, Bart
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description The Sampling/Importance Resampling (SIR) algorithm can be used for generating representative point sets from a distribution known up to a multiplicative constant. Moreover, the Quasi‐random Sampling Importance Resampling (QSIR) scheme, based on quasi‐Monte Carlo methods, is a recent modification of the SIR algorithm and was empirically shown to have better convergence. We present error convergence results for QSIR that we obtained using quasi‐Monte Carlo theory. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
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title On the convergence of quasi-random sampling importance resampling
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