on the convergence of quasi-random sampling/importance resampling

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.