A Normal Approximation for the Multivariate Likelihood Ratio Statistics.

Abstract

For many multivariate hypotheses, under the normality assumptions, the likelihood ratio tests are optimal in the sense of having maximal exact slopes. The exact distributions needed for implementing these tests are complex and their tabulation is limited in scope and accessibility. In this paper, a method of constructing normal approximations to these distributions is described, and illustrated using the problems of testing sphericity and independence between two sets of variates. The normal approximations are compared with well known competing approximations and are seen to fare well. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1980
Accession Number
ADA095874

Entities

People

  • Govind S. Mudholkar
  • Madhusudan C. Trivedi

Organizations

  • University of Rochester

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Computer Programs
  • Data Analysis
  • Data Mining
  • Data Science
  • Distribution Theory
  • Hypotheses
  • Information Science
  • Multivariate Analysis
  • New York
  • Normal Distribution
  • Normality
  • Probability
  • Random Variables
  • Statistical Analysis
  • Statistical Tests
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Systems Analysis and Design