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Beta Variate Generation via Exponential Majorizing Functions

Author

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  • Bruce W. Schmeiser

    (Southern Methodist University, Dallas, Texas)

  • A. J. G. Babu

    (Southern Methodist University, Dallas, Texas)

Abstract

Two acceptance/rejection algorithms for generating random variates from the beta distribution are developed. The algorithms use piece-wise linear and exponential majorizing functions coupled with a piece-wise linear minorizing function. The algorithms are exact to within the accuracy of the computer and are valid for all parameter values greater than one Marginal execution times are relatively insensitive to parameter values and are faster than any previously published algorithms.

Suggested Citation

  • Bruce W. Schmeiser & A. J. G. Babu, 1980. "Beta Variate Generation via Exponential Majorizing Functions," Operations Research, INFORMS, vol. 28(4), pages 917-926, August.
    • Handle: RePEc:inm:oropre:v:28:y:1980:i:4:p:917-926
    DOI: 10.1287/opre.28.4.917
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    Cited by:

    1. Cheng, Ching-Wei & Hung, Ying-Chao & Balakrishnan, Narayanaswamy, 2014. "Generating beta random numbers and Dirichlet random vectors in R: The package rBeta2009," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1011-1020.
    2. Elena Almaraz Luengo & Carlos Gragera, 2023. "Critical Analysis of Beta Random Variable Generation Methods," Mathematics, MDPI, vol. 11(24), pages 1-31, December.

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