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Randomly Permuted (t,m,s)-Nets and (t, s)-Sequences

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Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing

Part of the book series: Lecture Notes in Statistics ((LNS,volume 106))

Abstract

This article presents a hybrid of Monte Carlo and Quasi-Monte Carlo methods. In this hybrid, certain low discrepancy point sets and sequences due to Faure, Niederreiter and Sobol’ are obtained and their digits are randomly permuted. Since this randomization preserves the equidistribution properties of the points it also preserves the proven bounds on their quadrature errors. The accuracy of an estimated integrand can be assessed by replication, consisting of independent re-randomizations.

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Author information

Authors and Affiliations

  1. Dept. of Statistics, Sequoia Hall Stanford University, Stanford, CA, 94305, USA

    Art B. Owen

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  1. Art B. Owen
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Editor information

Editors and Affiliations

  1. Institüt für Informationsverabeitung, Osterreichische Akademie der Wissenschaften, Sonnenfelsgasse 19/2, A-1010, Wien, Austria

    Harald Niederreiter

  2. Department of Mathematical Sciences, University of Nevada, Las Vegas, 89154, Las Vegas, Nevada, USA

    Peter Jau-Shyong Shiue

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© 1995 Springer-Verlag New York, Inc.

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Owen, A.B. (1995). Randomly Permuted (t,m,s)-Nets and (t, s)-Sequences. In: Niederreiter, H., Shiue, P.JS. (eds) Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing. Lecture Notes in Statistics, vol 106. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2552-2_19

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  • DOI: https://doi.org/10.1007/978-1-4612-2552-2_19

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-94577-4

  • Online ISBN: 978-1-4612-2552-2

  • eBook Packages: Springer Book Archive

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