Statistical Tests of Some Widely Used and Recently Proposed Uniform Random Number Generators

Abstract

Several widely used uniform random number generators have been extensively subjected to three commonly used statistical tests of uniformity and randomness. The object was (1) to examine the power of these statistical tests to discriminate between good and bad random number generators, (2) to correlate these results with recently proposed mathematical characterizations of random number generators which might also be useful in such a discrimination, and (3) to examine the effect of shuffling on the random number generators. Briefly the results show that the commonly used runs test has virtually no power to discriminate between good and bad generators, while serial tests perform better. Also shuffling does help, although much more needs to be done in this area. And finally, there is some utility to the mathematical characterizations, but many unanswered questions.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1973
Accession Number
AD0773747

Entities

People

  • G. P. Learmonth
  • P. A. Lewis

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • California
  • Chi Square Test
  • Computer Programming
  • Computer Science
  • Computers
  • Data Science
  • Distribution Theory
  • Feedback
  • Information Science
  • Pseudo Random Sequences
  • Random Number Generators
  • Sequences
  • Shift Registers
  • Simulations
  • Statistical Tests
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Educational Psychology
  • Statistical inference.