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A Simple and Efficient Algorithm to Compute Tail Probabilities from Transforms

Author

Listed:
  • Loren K. Platzman

    (Georgia Institute of Technology, Atlanta, Georgia)

  • Jane C. Ammons

    (Georgia Institute of Technology, Atlanta, Georgia)

  • John J. Bartholdi

    (Georgia Institute of Technology, Atlanta, Georgia)

Abstract

We present an algorithm to approximately compute the “tail” probability that a random variable exceeds a specified number, given only an expression for its transform. We also show that the problem is #P-hard (more difficult than NP-hard), suggesting that no efficient procedure can solve it exactly. Our method consists essentially of summing a power series, and thus is easy to perform and requires little memory. Furthermore, its computational effort is nearly linear in the reciprocal of a prespecified worst-case error bound.

Suggested Citation

  • Loren K. Platzman & Jane C. Ammons & John J. Bartholdi, 1988. "A Simple and Efficient Algorithm to Compute Tail Probabilities from Transforms," Operations Research, INFORMS, vol. 36(1), pages 137-144, February.
  • Handle: RePEc:inm:oropre:v:36:y:1988:i:1:p:137-144
    DOI: 10.1287/opre.36.1.137
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    Cited by:

    1. Roberto Cominetti & José R. Correa & Thomas Rothvoß & Jaime San Martín, 2010. "Optimal Selection of Customers for a Last-Minute Offer," Operations Research, INFORMS, vol. 58(4-part-1), pages 878-888, August.

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