Entropy-Based Random Number Evaluation

Abstract

Recent work has shown how to test a simple hypothesis of uniformity on the interval (0, 1) by using estimates of entropy. In this paper we use Monte Carlo methods to extend previous tables of critical points and power for such entropy tests to the large sample sizes likely to be desirable when evaluating the output of one or more random number generators. A comparison with asymptotic critical points and power is made. The results are used to evaluate a number of commonly used random number generators. At least one random number generator judged 'good' by the spectral test (multiplier 5**15) is found unsuitable for use. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1981
Accession Number
ADA099397

Entities

People

  • Edward C. Van Der Meulen
  • Edward J. Dudewicz
  • K. W. Teoh
  • M. G. Sriram

Organizations

  • Ohio State University

Tags

DTIC Thesaurus Topics

  • Asymptotic Normality
  • Contracts
  • Data Science
  • Distribution Functions
  • Estimators
  • Generators
  • Information Science
  • Military Research
  • Monte Carlo Method
  • Normal Distribution
  • Random Number Generators
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Samples
  • Statistics
  • Step Functions
  • Test And Evaluation

Fields of Study

  • Mathematics

Readers

  • Electrical Engineering
  • Regression Analysis.
  • Statistical inference.