Relationships among Various Kinds of Eigenvalue and Singular Value Decompositions

Eigenvalue decomposition (EVD) and/or singular value decomposition (SVD) play important roles in many multivariate data analysis techniques as computational tools for dimension reduction. A variety of EVD and SVD have been developed to deal with specific kinds of dimension reduction problems. This paper explicates various relationships among those decompositions with the prospect of exploiting them in practical applications of multivariate analysis.

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