Poisson Random Variate Generation.

Abstract

Approximate algorithms have long been the only available methods for generating Poisson random variates when the mean is large. A new algorithm is developed that is exact, has execution time insensitive to the value of the mean, and is valid whenever the mean is greater than ten. This algorithm is compared to the three other algorithms which have been developed recently for generating Poisson variates when the mean is large. Criteria used are set-up time, marginal execution time, memory requirements, and lines of code. New simple tight bounds on Poisson probabilities contribute to the speed of the algorithm, but are useful in a general context. In addition, Poisson variate generation is surveyed. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1981
Accession Number
ADA111883

Entities

People

  • Bruce Schmeiser
  • Voratas Kachitvichyanukul

Organizations

  • Purdue University

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Computers
  • Demographic Cohorts
  • Discrete Distribution
  • Engineering
  • Equations
  • Generators
  • Industrial Engineering
  • Inequalities
  • Military Research
  • Normal Distribution
  • Numbers
  • Probability
  • Random Number Generators
  • Random Variables
  • Rejection

Fields of Study

  • Mathematics

Readers

  • Computer Programming and Software Development.
  • Operations Research
  • Plasma Physics / Magnetohydrodynamics