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Stochastic Programming 84 Part I pp 17–38Cite as

Multidimensional numerical integration using pseudorandom numbers

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Part of the book series: Mathematical Programming Studies ((MATHPROGRAMM,volume 27))

Abstract

Practical implementations of Monte Carlo methods for multidimensional numerical integration use nodes derived from pseudorandom numbers. We present effective error bounds for Monte Carlo integration with nodes derived from the two most common types of pseudorandom numbers, namely linear congruential pseudorandom numbers and Tausworthe pseudorandom numbers. We compare the results with those obtained by the use of quasirandom nodes.

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Authors and Affiliations

  1. Mathematical Institute, Austrian Academy of Sciences, Dr. Ignaz-Seipel-Platz 2, A-1010, Vienna, Austria

    Harald Niederreiter

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  1. Harald Niederreiter
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Andras Prékopa Roger J.- B. Wets

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© 1986 The Mathematical Programming Society, Inc.

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Niederreiter, H. (1986). Multidimensional numerical integration using pseudorandom numbers. In: Prékopa, A., Wets, R.J.B. (eds) Stochastic Programming 84 Part I. Mathematical Programming Studies, vol 27. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0121112

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  • DOI: https://doi.org/10.1007/BFb0121112

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00924-2

  • Online ISBN: 978-3-642-00925-9

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