On the Behavior of Prior Distributions Fitted to Failure Data.

Abstract

Equipment mean time between failures (MTBF) is assumed to be a random variable, the probability density function of the MTBF being called the prior density. The method of moments procedure for fitting the uniform prior density to failure data is given. The goodness of fit of the uniform prior is compared to the goodness of fit of the inverted gamma prior for actual failure data. Posterior producer's and consumer's risks for the uniform and inverted gamma priors are compared in the context of Bayesian reliability demonstration tests. It is shown that the corresponding posterior risks for the two priors can be significantly different even when the two priors fit the data equally well.

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1975
Accession Number
ADA020677

Entities

People

  • C. P. Tsokos
  • J. J. Higgins

Organizations

  • University of South Florida

Tags

DTIC Thesaurus Topics

  • Data Science
  • Demonstrations
  • Information Science
  • Mathematics
  • Method Of Moments
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Reliability
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference