Complete Independence in the Multivariate Normal Distribution.

Abstract

Testing complete independence is one of the simplest problems concerning the covariance structure of a set of measurements. A stepwise procedure proposed by S. N. Roy and R. E. Bargmann (1958) and a trace criterion due to H. Nagao (1973) are two well known competitors of the likelihood ratio test of the hypothesis derived assuming the multivariate normality. We consider some modifications of the Roy-Bargmann procedure based on combinations of independent tests and find them to be asymptotically equivalent to the likelihood ratio test, which is optimal in terms of the exact slopes. The operating characteristics of various tests with samples of moderate size are examined empirically. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1980
Accession Number
ADA095871

Entities

People

  • Govind S. Mudholkar
  • Perla Subbaiah

Organizations

  • University of Rochester

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Applied Mathematics
  • Covariance
  • Data Science
  • Distribution Functions
  • Governments
  • Information Science
  • Monotone Functions
  • New York
  • Normal Distribution
  • Probability
  • Statistical Algorithms
  • Statistical Samples
  • Statistical Tests
  • Statistics
  • United States
  • United States Government

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.