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- W2139702961 abstract "Influence functions [2] of the most important parameters in principal component analysis (PCA), e.g., eigenvalues, eigenvectors and projection operators, have been derived by a number of authors [1,3,7] using results from the perturbation theory of the ordinary eigenproblem. In the present paper we show that the perturbation theory of generalized eigenproblems [4] underlies and unifies the treatment of influence functions of eigenvalues and eigenvectors in multidimensional data analysis and we present new applications in canonical variate (CVA) and canonical correlation analysis (CCA)." @default.
- W2139702961 created "2016-06-24" @default.
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- W2139702961 date "1990-01-01" @default.
- W2139702961 modified "2023-09-24" @default.
- W2139702961 title "Influence Functions of Eigenvalues and Eigenvectors in Multidimensional Data Analysis" @default.
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- W2139702961 doi "https://doi.org/10.1007/978-3-642-50096-1_33" @default.
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