Goodness of Fit Tests for the Weibull and the Extreme Value Distribution with Estimated Parameters.

Abstract

In this paper we consider the problem of testing the null hypothesis that a given random sample belongs to a Weibull of an extreme value distribution with unknown parameters. The test statistics are those based on the empirical distribution function, and tables of critical values are provided. The asymptotic points have been obtained by a pooling of two methods. In the first method the percentage points for finite n are plotted and extrapolated to infinity. In the second method, the appropriate asymptotic process is simulated and its percentiles, which give the critical points, thus estimated. Some difficulties in simulating the asymptotic process are discussed, and a comparison between two methods is discussed. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Nov 20, 1979
Accession Number
ADA096981

Entities

People

  • Mahesh Chandra
  • Michael A. Stephens
  • Nozer Singpurwalla

Organizations

  • George Washington University

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Data Science
  • Distribution Functions
  • Engineering
  • Gaussian Processes
  • Goodness Of Fit Tests
  • Information Processing
  • Information Science
  • Knowledge Management
  • Military Research
  • Monte Carlo Method
  • New York
  • Random Variables
  • Sampling
  • Statistical Algorithms
  • Statistics
  • Stochastic Processes
  • Test And Evaluation

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.