Characterizations and Goodness of Fit Tests.

Abstract

In this article a systematic approach to providing goodness of fit tests is discussed, for the composite goodness of fit problem of testing that the distribution F of a random sample comes from a parametric family F sub O. Characterization procedures are emphasized, and it is shown that, at least for the exponential case, invariant characterizations appear to be better than those which are not invariant. A general technique is developed for producing invariant characterizations and for the exponential case it is shown how these are related to characterizations already in the literature. Power studies are given to examine the tests based on both invariant and non-invariant characterizations. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 02, 1981
Accession Number
ADA102167

Entities

People

  • Federico J. O'reilly
  • Michael A. Stephens

Organizations

  • Stanford University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Composite Materials
  • Data Science
  • Distribution Functions
  • Goodness Of Fit Tests
  • Information Science
  • Integrals
  • Military Research
  • Normal Distribution
  • Order Statistics
  • Probability
  • Probability Distributions
  • Random Variables
  • Statistical Samples
  • Statistics
  • United States
  • United States Government
  • Universities

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Statistical inference.