Topics in Model Building. Part III. Posterior Probabilities of Candidate Models in Model Discrimination.

Abstract

Procedures are discussed for obtaining the posterior probability for each of the candidate models in model discrimination when a prior state of indifference concerning the unknown parameter exists. The first argument makes use of information theory and arrives at the result of Box and Henson. Two additional ways of reasoning are introduced for the special case where the number of unknown parameters is identical in all the models. It is shown that these additional approaches both lead to results which are similar to the original result. (Author)

Document Details

Document Type
Technical Report
Publication Date
May 01, 1973
Accession Number
AD0770967

Entities

People

  • H. Kanemasu

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Discrimination
  • Ergodic Processes
  • Information Theory
  • Mathematics
  • Probability
  • Reasoning
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Regression Analysis.