Canonical correlation analysis based on information theory

Authors:
Xiangrong Yin
Affiliations:
Department of Statistics, University of Georgia, 204 Statistics Building, Athens, GA
Venue:
Journal of Multivariate Analysis
Year:
2004

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Abstract

In this article, we propose a new canonical correlation method based on information theory. This method examines potential nonlinear relationships between p × 1 vector Y-set and q × 1 vector X-set. It finds canonical coefficient vectors a and b by maximizing a more general measure, the mutual information, between aTX and bTY. We use a permutation test to determine the pairs of the new canonical correlation variates, which requires no specific distributions for X and Y as long as one can estimate the densities of aTX and bTY nonparametrically. Examples illustrating the new method are presented.