Comparison of Bayes Estimates of Failure Intensity for Fitted Priors of Life Data.

Abstract

The number of times a piece of equipment fails in a fixed time T is assumed to have the Poisson sampling density. The parameter of interest is the failure intensity, the reciprocal of the mean time between failures. The loss function of interest is the squared error loss function. A robustness study of Bayes estimates of the failure intensity is carried out. The Bayes estimate of the failure intensity for a general prior is expressed in terms of the marginal density of the observed number of failures, and implications for the robustness of Bayes estimates for fitted priors is discussed. Numerical examples are given for the gamma, uniform, and inverted uniform priors which are fitted to actual failure data. In addition to comparisons among the Bayes estimates of failure intensity for fitted priors, the Bayes estimate under the fitted gamma prior is compared to the corresponding estimates under other, subjectively chosen, gamma priors.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1976
Accession Number
ADA020674

Entities

People

  • C. P. Tsokos
  • J. J. Higgins

Organizations

  • University of South Florida

Tags

DTIC Thesaurus Topics

  • Intensity

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

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