Recent Advances in Statistical Methods for System Reliability Using Bernoulli Sampling of Components

Abstract

The paper provides a survey of results in statistical inference in systems reliability using Bernoulli sampling of individual components. Particular attention is given to the notion of Buehler optimality and its implementation in such problems. Recent results of the authors on Buehler optimal confidence bounds on the reliability of series and parallel systems are discussed. For series systems, these results employ a generalization of an inequality of Sudakov. For parallel systems, Buehler optimal bounds are obtained for small numbers of failures using the notion of Schur concavity. Estimates of the optimal bounds are obtained in those cases for which the property of Schur concavity does not hold.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1981
Accession Number
ADA114495

Entities

People

  • Andrew P. Soms
  • Bernard Harris

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Computations
  • Confidence Limits
  • Contracts
  • Data Science
  • Estimators
  • High Reliability
  • Inequalities
  • Information Science
  • Mathematics
  • Military Research
  • Probability
  • Reliability
  • Sampling
  • Statistical Inference
  • Statistics
  • Surveys
  • United States

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

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