Asymptotic distributions of functions of the eigenvalues of sample covariance matrix and canonical correlation matrix in multivariate time series

Masanobu Taniguchi, P. R. Krishnaiah

Research output: Contribution to journalArticle

4 Citations (Scopus)


Let S = (1/n) Σt=1 n X(t) X(t)′, where X(1), ..., X(n) are p × 1 random vectors with mean zero. When X(t) (t = 1, ..., n) are independently and identically distributed (i.i.d.) as multivariate normal with mean vector 0 and covariance matrix Σ, many authors have investigated the asymptotic expansions for the distributions of various functions of the eigenvalues of S. In this paper, we will extend the above results to the case when {X(t)} is a Gaussian stationary process. Also we shall derive the asymptotic expansions for certain functions of the sample canonical correlations in multivariate time series. Applications of some of the results in signal processing are also discussed.

Original languageEnglish
Pages (from-to)156-176
Number of pages21
JournalJournal of Multivariate Analysis
Issue number1
Publication statusPublished - 1987
Externally publishedYes



  • asymptotic distributions
  • canonical correlation matrix
  • eigenvalues
  • sample covariance matrix
  • time series

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Numerical Analysis
  • Statistics and Probability

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