Canonical correlation analysis based on information theory
In this article, we propose a new canonical correlation method based on information theory. This method examines potential nonlinear relationships between px1 vector Y-set and qx1 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.
Year of publication: |
2004
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Authors: | Yin, Xiangrong |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 91.2004, 2, p. 161-176
|
Publisher: |
Elsevier |
Keywords: | Canonical correlation analysis Multivariate analysis Mutual information Permutation test |
Saved in:
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