CANONICAL CORRELATION ANALYSIS IN THE CASE OF MULTIVARIATE REPEATED MEASURES DATA

Krzysko Mirosław (), Łukaszonek Wojciech () and Wołynski Waldemar ()
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Krzysko Mirosław: Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poland
Łukaszonek Wojciech: Interfaculty Institute of Mathematics and Statistics, The President Stanistaw Wojciechowski State University of Applied Sciences, Kalisz, Poland
Wołynski Waldemar: Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poland

Statistics in Transition New Series, 2018, vol. 19, issue 1, 75-85

Abstract: In this paper, we present, in the real example, canonical variables applicable in the case of multivariate repeated measures data under the following assumptions: (1) multivariate normality for the vector of observations and (2) Kronecker product structure of the positive definite covariance matrix. These variables are especially useful when the number of observations is not large enough to estimate the covariance matrix, and thus the traditional canonical variables fail. Computational schemes for maximum likelihood estimates of required parameters are also given.

Keywords: canonical correlation analysis; repeated measures data (doubly multivariate data); Kronecker product covariance structure; maximum likelihood estimates. (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:19:y:2018:i:1:p:75-85:n:7

DOI: 10.21307/stattrans-2018-005

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