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Quasi Importance Sampling

By Wolfgang Hörmann and Josef Leydold


There arise two problems when the expectation of some function with respect to a nonuniform multivariate distribution has to be computed by (quasi-) Monte Carlo integration: the integrand can have singularities when the domain of the distribution is unbounded and it can be very expensive or even impossible to sample points from a general multivariate distribution. We show that importance sampling is a simple method to overcome both problems. (author's abstract)Series: Preprint Series / Department of Applied Statistics and Data Processin

Topics: MSC 65C05, 65C10, 65D32, quasi-Monte Carlo method / nonuniform random variate generation / inversion method / importance sampling / Markov chain Monte Carlo
Publisher: Department of Statistics and Mathematics, Abt. f. Angewandte Statistik u. Datenverarbeitung, WU Vienna University of Economics and Business
Year: 2005
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