EXACT BAYESIAN TESTS OF SHARP HYPOTHESES.

Abstract

The Bayesian theory for testing a hypothesis defined by fixed values of parameters is presented in general terms without approximations. Arbitrary positive prior probability is attached to the hypothesis. The conditional distribution of the nuisance parameters given the parameters defining the hypothesis is assumed to be continuous in the latter at their values for the hypothesis. Families of integrable conjugate prior distributions are assigned under the alternative hypothesis for the problem of equality of Bernoulli parameters, for multivariate extensions, and for multivariate normal problems. (Author)

Document Details

Document Type
Technical Report
Publication Date
Oct 07, 1968
Accession Number
AD0680109

Entities

People

  • B. P. Lientz
  • James M. Dickey
  • V. K. Marthy

Organizations

  • System Development Corporation

Tags

DTIC Thesaurus Topics

  • Hypotheses
  • Probability

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms