Nonparametric Estimation and Goodness of Fit Testing of Hypotheses for Distributions in Accelerated Life Testing,

Abstract

In this paper we present a nonparametric approach to accelerated life testing by deleting the requirement that the common parametric family of life distributions under all the stresses be specified in advance. We do retain the requirement that the time transformation function be specified, and consider a version of the familiar inverse power law. We show how the data from the accelerated life test can be used to obtain a consistent estimate of the failure distribution at use conditions stress, and test the hypotheses that the underlying failure distributions belong to a specified family of distributions. We also show how to obtain approximate uniform confidence bounds for the failure distribution at use conditions stress. We illustrate our approach by considering some real life data. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 25, 1980
Accession Number
ADA099431

Entities

People

  • Moshe Shaked
  • Nozer Singpurwalla

Organizations

  • George Washington University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Computer Programs
  • Confidence Limits
  • Data Science
  • Distribution Functions
  • Engineering
  • Goodness Of Fit Tests
  • Information Science
  • Life Tests
  • Logistics Management
  • Military Research
  • New York
  • Probability
  • Random Variables
  • Reliability
  • Security
  • Statistics
  • Test And Evaluation

Fields of Study

  • Mathematics

Readers

  • Linear Algebra
  • Regression Analysis.
  • Structural Health Monitoring of Composite Structures.