A Comparison of the Accuracy of Univariate and Bivariate Techniques for Finding the Lower Confidence Limits of System Reliability.

Abstract

The purpose of this thesis is to compare the accuracy of two Monte Carlo simulation techniques of finding lower system reliability confidence limits: the bivariate technique and the univariate technique. The actual results compared are the confidence interval coverages of the true system reliability associated with the confidence limits. The bivariate technique is based upon the assumption that the maximum likelihood estimators of the component shape and scale parameters have an asymptotic normal distribution. The univariate technique uses the assumption that the component reliability estimates have a normal distribution. Two variations of the univariate technique are also examined. The first variations assumes that component reliability estimates follow a beta distribution instead of a normal distribution. The second variation replaces all perfect system reliability estimates with new, adjusted reliability values.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1980
Accession Number
ADA094810

Entities

People

  • Kathleen Mary Depuy

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Advanced Electronics
  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Computer Programs
  • Confidence Limits
  • Data Science
  • Distribution Functions
  • Electronic Components
  • Electronic Equipment
  • Estimators
  • Information Processing
  • Information Science
  • Life Tests
  • Materials
  • Monte Carlo Method
  • Normal Distribution
  • Probability Distributions
  • Random Variables
  • Statistical Algorithms

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.