Canonical correlation analysis  in the case of multivariate repeated measures data

Mirosław  Krzyśko; Wojciech  Łukaszonek; Waldemar  Wołyński

Canonical correlation analysis in the case of multivariate repeated measures data

Mirosław Krzyśko Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poland. Interfaculty Institute of Mathematics and Statistics, The President Stanisław Wojciechowski State University of Applied Sciences in Kalisz, Poland. , Wojciech Łukaszonek Interfaculty Institute of Mathematics and Statistics, The President Stanisław Wojciechowski State University of Applied Sciences in Kalisz, Poland. , Waldemar Wołyński Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poland. Statistics in Transition new series, vol. 19, 2018, 1, pages: 75-86 Published online: 1 March 2018

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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.

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