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Generating Pseudorandom Numbers

  • Chapter
Monte Carlo

Part of the book series: Springer Series in Operations Research ((ORFE))

Abstract

Every Monte Carlo experiment relies on the availability of a procedure that supplies sequences of numbers from which arbitrarily selected nonoverlapping subsequences appear to behave like statistically independent sequences and where the variation in an arbitrarily chosen subsequence of length k (≥1) resembles that of a sample drawn from the uniform distribution on the k-dimensional unit hyper-cube \({\mathcal{I}^k}\). The words “appear to behave” and “resemble” alert the reader to yet another potential source of error that arises in Monte Carlo sampling. In practice, many procedures exist for generating these sequences. In addition to this error of approximation, the relative desirability of each depends on its computing time, on its ease of use, and on its portability By portability, we mean the ease of implementing a procedure or algorithm on a variety of computers, each with its own hardware peculiarities.

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Authors and Affiliations

  1. Department of Operations Research, University of North Carolina, 27599-3180, Chapel Hill, NC, USA

    George S. Fishman

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  1. George S. Fishman
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© 1996 Springer Science+Business Media New York

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Fishman, G.S. (1996). Generating Pseudorandom Numbers. In: Monte Carlo. Springer Series in Operations Research. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-2553-7_7

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  • DOI: https://doi.org/10.1007/978-1-4757-2553-7_7

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-2847-4

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