A Bayesian Nonparametric Approach to Reliability.

Abstract

It is suggested that problems in a reliability context may be handled by a Bayesian non-parametric approach. A stochastic process is defined whose sample paths may be assumed to be either increasing hazard rates or decreasing hazard rates by properly choosing the parameter functions of the process. The posterior distribution of the hazard rates are derived for both exact and censored data. Bayes estimates of hazard rates,c.d.f.'s, densities, and means, are found under squared error type loss functions. Some simulation is done and estimates graphed to better understand the estimators. Finally, estimates of the c.d.f. from some data in a paper by Kaplan and Meier are constructed. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 10, 1979
Accession Number
ADA072431

Entities

People

  • Purushottam Laud
  • Richard L. Dykstra

Tags

DTIC Thesaurus Topics

  • Computations
  • Estimators
  • Integrals
  • Military Research
  • Missouri
  • Numbers
  • Observation
  • Probability
  • Random Variables
  • Reliability
  • Statistical Inference
  • Statistics
  • Stochastic Processes
  • Survival
  • Theorems
  • United States
  • United States Government

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

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