Effect of Additional Variables in Principal Component Analysis, Discriminant Analysis and Canonical Correlation Analysis.

Abstract

In this paper, the authors derived asmptotic distributions of changes in certain functions of the eigenvalues of the sample covariance matrix, MANOVA matrix and canonical correlation matrix when some variables are added to the original sets of variables. The above results are useful in finding out as to whether the new variables give additional information for statistical inference; multivariate analysis; Wishart distribution. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1985
Accession Number
ADA162069

Entities

People

  • J. Schmidhammer
  • Paruchuri R. Krishnaiah
  • Y. Fujikoshi

Organizations

  • University of Pittsburgh

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Air Force
  • Analysis Of Variance
  • Correlation Analysis
  • Covariance
  • Data Science
  • Discriminant Analysis
  • Eigenvalues
  • Factor Analysis
  • Governments
  • Information Science
  • Multivariate Analysis
  • Scientific Research
  • United States
  • United States Government
  • Universities

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms