On the convergence of quasi-random sampling/importance resampling

摘要

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.