Abstract
Most applications of quasi-Monte Carlo methods in numerical analysis are in evaluating high dimensional integrals. However, many problems in statistics, that are not obvious integration problems, need low-discrepancy sequences/sets that can be generated by Quasi-Monte Carlo methods. In this paper we review some applications of low-discrepancy sequences/sets in statistical inference, Bayesian statistics, geometric probability and experimental design. Furthermore, measures of uniformity can be regarded as an important criterion in statistical experimental design. We also review various applications of uniformity in factorial design, block design and others.
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