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Estimating common principal components in high...
Journal article

Estimating common principal components in high dimensions

Abstract

We consider the problem of minimizing an objective function that depends on an orthonormal matrix. This situation is encountered, for example, when looking for common principal components. The Flury method is a popular approach but is not effective for higher dimensional problems. We obtain several simple majorization–minimization (MM) algorithms that provide solutions to this problem and are effective in higher dimensions. We use mixture …

Authors

Browne RP; McNicholas PD

Journal

Advances in Data Analysis and Classification, Vol. 8, No. 2, pp. 217–226

Publisher

Springer Nature

Publication Date

June 2014

DOI

10.1007/s11634-013-0139-1

ISSN

1862-5347

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