Estimation of Reliability in a Multicomponent Stress-Strength Model.

Abstract

A stress-strength model is formulated for s out of k systems consisting of identical components. The authors consider minimum variance unbiased estimation of system reliability for data consisting of a random sample from the stress distribution and one from the strength distribution when the two distributions are related as Lehmann alternatives. The asymptotic distribution is obtained by expanding the unbiased estimate about the maximum likelihood value and establishing their equivalence. Performance of the two estimates for moderate samples is studied by Monte Carlo simulation. Uniformly most accurate unbiased confidence intervals are also obtained for system reliability. (Author)

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1973
Accession Number
AD0770979

Entities

People

  • G. K. Bhattacharyya
  • Richard A. Johnson

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Computing-Related Activities
  • Data Science
  • Information Science
  • Interdisciplinary Science
  • Intervals
  • Mathematical Analysis
  • Mathematics
  • Monte Carlo Method
  • Reliability
  • Simulations
  • Statistical Samples

Fields of Study

  • Mathematics

Readers

  • Statistical inference.