Acceptance-Rejection Techniques for Sampling from The Gamma and Beta Distributions.

Abstract

John von Neumann's idea of sampling from a distribution by majorizing its probability density function is applied to gamma and beta distributions. Optimum envelopes are constructed resulting in sampling algorithms whose performance will not deteriorate when the parameters are increased. In some methods the process of acceptance is accelerated. For this the employed test functions are replaced in most cases with simpler bounds which are difficult to derive but easy to apply. The reported computational experience indicates that the new methods can be of considerable practical use. (Author)

Document Details

Document Type
Technical Report
Publication Date
May 29, 1974
Accession Number
AD0782478

Entities

People

  • J. H. Ahrens
  • U. Dieter

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Cooperation
  • Data Science
  • Information Science
  • Mathematics
  • Nova Scotia
  • Probability
  • Probability Density Functions
  • Random Variables
  • Rejection
  • Sampling
  • Statistical Algorithms

Readers

  • Statistical inference.
  • Systems Analysis and Design