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Rectangles algorithm for generating normal variates

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  • Rui Zhang
  • Lawrence M. Leemis

Abstract

We propose an algorithm for generating normal random variates that is based on the acceptance–rejection method and uses a piecewise majorizing function. The piecewise function has 2048 equal‐area pieces, 2046 of which are constant, and the two extreme pieces are curves that majorize the tails. The proposed algorithm has not only good performance from correlation induction perspective, but also works well from a speed perspective. It is faster than the inversion method by Odeh and Evans and most other methods. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011

Suggested Citation

  • Rui Zhang & Lawrence M. Leemis, 2012. "Rectangles algorithm for generating normal variates," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(1), pages 52-57, February.
    • Handle: RePEc:wly:navres:v:59:y:2012:i:1:p:52-57
    DOI: 10.1002/nav.21474
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    References listed on IDEAS

    as
    1. Marsaglia, George & Tsang, Wai Wan, 2000. "The Ziggurat Method for Generating Random Variables," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 5(i08).
    2. R. E. Odeh & J. O. Evans, 1974. "The Percentage Points of the Normal Distribution," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 23(1), pages 96-97, March.
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