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Monte Carlo, Quasi-Monte Carlo, and Randomized Quasi-Monte Carlo

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Monte-Carlo and Quasi-Monte Carlo Methods 1998

Abstract

This paper surveys recent research on using Monte Carlo techniques to improve quasi-Monte Carlo techniques. Randomized quasi-Monte Carlo methods provide a basis for error estimation. They have, in the special case of scrambled nets, also been observed to improve accuracy. Finally through Latin supercube sampling it is possible to use Monte Carlo methods to extend quasi-Monte Carlo methods to higher dimensional problems.

This paper describes a talk prepared for the June 1998 MCQMC’98 meeting in Claremont CA, and for the December 1998 WSC’98 meeting in Washington DC. Apart from a brief epilogue, this paper originally appeared as “Monte Carlo Extension of Quasi-Monte Carlo” in the Proceedings of 1998 Winter Simulation Conference (D. J. Medieiros, E.F. Watson, M. Manivannan, and J. Carson, Eds.), pages 571–577. I thank WSC’98 for allowing its republication.

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Author information

Authors and Affiliations

  1. Department of Statistics, Stanford University, Stanford, CA, 94305, USA

    Art B. Owen

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  1. Art B. Owen
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Editors and Affiliations

  1. Institute of Discrete Mathematics, Austrian Academy of Sciences, Sonnenfelsgasse 19, 1010, Vienna, Austria

    Harald Niederreiter

  2. Claremont Graduate University, 925 N. Dartmouth Avenue, 91711, Claremont, CA, USA

    Jerome Spanier

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Owen, A.B. (2000). Monte Carlo, Quasi-Monte Carlo, and Randomized Quasi-Monte Carlo. In: Niederreiter, H., Spanier, J. (eds) Monte-Carlo and Quasi-Monte Carlo Methods 1998. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59657-5_5

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  • DOI: https://doi.org/10.1007/978-3-642-59657-5_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66176-4

  • Online ISBN: 978-3-642-59657-5

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