BAYESIAN ANALYSIS OF THE WEIBULL PROCESS WITH UNKNOWN SCALE PARAMETER.

Abstract

The Weibull process with unknown scale parameter is taken as a model for Bayesian decision making. The family of natural conjugate prior distributions for the scale parameter is exhibited and used in prior and posterior analysis. Preposterior analysis and several sampling schemes are then discussed. Preposterior analysis is given for a two-action problem with utility linear in the unknown mean of the Weibull process, in which the sampling scheme yields the first r failures in a life test of n items. An example is included. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1966
Accession Number
AD0643816

Entities

People

  • Richard M. Soland

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Collecting Methods
  • Life Expectancy (Service Life)
  • Life Tests
  • Sampling

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

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