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Fast Generation of Randomized Low-Discrepancy Point Sets

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Monte Carlo and Quasi-Monte Carlo Methods 2000

Abstract

We introduce two novel techniques for speeding up the generation of digital (t,s)-sequences. Based on these results a new algorithm for the construction of Owen's randomly permuted (t,s)—sequences is developed and analyzed. An implementation is available at http://www. mcqmc. org/Sof tware. html.

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Author information

Authors and Affiliations

  1. Computer Science Dept., California Institute of Technology, Pasadena, CA, 91125, USA

    Ilja Friedel

  2. Computer Science Dept., University of Kaiserslautern, D-67653, Kaiserslautern, Germany

    Alexander Keller

Authors
  1. Ilja Friedel
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  2. Alexander Keller
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Editor information

Editors and Affiliations

  1. Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China

    Kai-Tai Fang  & Fred J. Hickernell  & 

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

    Harald Niederreiter

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© 2002 Springer-Verlag Berlin Heidelberg

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Friedel, I., Keller, A. (2002). Fast Generation of Randomized Low-Discrepancy Point Sets. In: Fang, KT., Niederreiter, H., Hickernell, F.J. (eds) Monte Carlo and Quasi-Monte Carlo Methods 2000. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-56046-0_17

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  • DOI: https://doi.org/10.1007/978-3-642-56046-0_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42718-6

  • Online ISBN: 978-3-642-56046-0

  • eBook Packages: Springer Book Archive

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