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Monte Carlo and Quasi-Monte Carlo Methods 2006 pp 35–52Cite as

MCQMC Methods for Multivariate Statistical Distributions

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Summary

A review and comparison is presented for the use of Monte Carlo and Quasi-Monte Carlo methods for multivariate Normal and multivariate t distribution computation problems. Spherical-radial transformations, and separation-of-variables transformations for these problems are considered. The use of various Monte Carlo methods, Quasi-Monte Carlo methods and randomized Quasi-Monte Carlo methods are discussed for the different problem formulations and test results are summarized.

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Author information

Authors and Affiliations

  1. Mathematics Department, Washington State University, Pullman, WA, 99164-3113

    Alan Genz

Authors
  1. Alan Genz
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Ulm University, Albert-Einstein-Allee 11, 89069, Ulm, Germany

    Alexander Keller

  2. Department of Computer Science, University of Kaiserslautern, 67653, Kaiserslautern, Germany

    Stefan Heinrich

  3. Department of Mathematics, National University of Singapore, 2 Science Drive 2, Singapore, 117543, Republic of Singapore

    Harald Niederreiter

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Genz, A. (2008). MCQMC Methods for Multivariate Statistical Distributions. In: Keller, A., Heinrich, S., Niederreiter, H. (eds) Monte Carlo and Quasi-Monte Carlo Methods 2006. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74496-2_3

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