Sensitivity Analysis of the Bayesian Estimators of the Intensity Parameter and Reliability Function of the Poisson Failure Model.

Abstract

The Poisson failure model is studied under a stochastic behavior of the intensity parameter. Bayesian estimators of the life parameter and reliability function are summarized in which the natural conjugate is assigned as the prior distribution of the random parameter. The sensitivity of these estimators is obtained by assuming a true prior which is different from the assigned prior distribution. The authors employ the ratio of the average mean square errors as a measure of the robustness of the Bayes estimators when the true prior is different from the assumed natural conjugate. Both analytical and numerical results are given.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1976
Accession Number
ADA020676

Entities

People

  • A. N. V. Rao
  • C. P. Tsokos

Organizations

  • University of South Florida

Tags

DTIC Thesaurus Topics

  • Estimators
  • Intensity
  • Reliability
  • Sensitivity

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference