RELIABILITY ESTIMATION UNDER PLAUSIBLE ASSUMPTIONS

Abstract

Most analyses of reliability problems assume that the form of the underlying failure distribution(s) is known; the parameter may be assumed known or unknown. Families of failure distributions commonly used are the exponential, gamma, normal, and lognormal. An expository survey is presented of recent research in reliability estimation based on assumptions made not simply for mathematical convenience but because they correspond to the physical situation. The class of statistical problems considered thus lies somewhere between parametric problems (in which the underlying failure distributions are assumed known up to a finite number of parameters) and nonparametric problems (in which no information is assumed available concerning the underlying failure distributions).

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1965
Accession Number
AD0619873

Entities

People

  • Frank Proschan

Organizations

  • University of California, Berkeley

Tags

DTIC Thesaurus Topics

  • Binomials
  • California
  • Distribution Functions
  • Estimators
  • Inequalities
  • Life Tests
  • Maximum Likelihood Estimation
  • New York
  • Operations Research
  • Order Statistics
  • Probability
  • Probability Distributions
  • Random Variables
  • Reliability
  • Statistics
  • United States
  • Universities

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Theoretical Analysis.