On Some Goodness of Fit Tests for the Weibull Distribution with Estimated Parameters.

Abstract

This note considers some test statistics based on the sample distribution function for testing the null hypothesis that a random sample belongs to a Weibull distribution with unknown scale and shape parameters. A foundation for testing such a hypothesis is provided by the fact that the logarithm of a Weibull random variable has an extreme value distribution with a location and a scale parameter, and by results which pertain to the weak convergence of an associated empirical stochastic process, under the null hypothesis. The asymptotic distribution of the empirical process serves as a basis for Monte Carlo studies for determining the appropriate critical points of the test statistics.

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Document Details

Document Type
Technical Report
Publication Date
Oct 14, 1977
Accession Number
ADA046630

Entities

People

  • Mahesh Chandra
  • Nozer Singpurwalla

Organizations

  • George Washington University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Convergence
  • Data Science
  • Distribution Functions
  • Engineering
  • Estimators
  • Gaussian Processes
  • Goodness Of Fit Tests
  • Information Science
  • Knowledge Management
  • Random Variables
  • Schools
  • Statistical Samples
  • Statistics
  • Stochastic Processes
  • Universities
  • Weak Convergence

Fields of Study

  • Mathematics

Readers

  • Statistical inference.