Some Optimal Properties and Interpretations of Principal Components.

Abstract

Optimal properties are derived and some new geometrical interpretations given for principal components. Typically, our main results concern the simultaneous minimization of eigenvalues of certain covariance matrices which measure the goodness of an approximation. Many popular criteria like total variance and generalized variance, which are increasing functions of the eigenvalues, are then minimized by the best approximator. In other situations, the criterion may not be a monotone function of the eigenvalues. A general optimal class is derived based on the non-negative definite ordering of covariance matrices. Also a result is given for the sequential selection of principal components. In the final section gives a new geometrical interpretation of the sample principal components.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1978
Accession Number
ADA054555

Entities

People

  • Raul Hudlet
  • Richard A. Johnson

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Algebra
  • Covariance
  • Eigenvalues
  • Eigenvectors
  • Equations
  • Inequalities
  • Invariance
  • Mathematics
  • Monotone Functions
  • New York
  • North Carolina
  • Observation
  • Probability
  • Random Variables
  • Statistical Analysis
  • Statistics
  • United States

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Mathematical Modeling and Probability Theory.