Some Comments on Singular Value Decomposition Analysis
Open Access
- 1 July 1997
- journal article
- Published by American Meteorological Society in Journal of Climate
- Vol. 10 (7) , 1759-1761
- https://doi.org/10.1175/1520-0442(1997)010<1759:scosvd>2.0.co;2
Abstract
The singular value decomposition analysis (SVD) method is discussed in the context of the simultaneous orthogonal rotation of two matrices. It is demonstrated that the singular vectors are rotated EOFs and the SVD expansion coefficients are rotated sets of principal component expansion coefficients. This way of thinking about SVD aids in the interpretation of results and provides guidance as to when and how to use SVD. Abstract The singular value decomposition analysis (SVD) method is discussed in the context of the simultaneous orthogonal rotation of two matrices. It is demonstrated that the singular vectors are rotated EOFs and the SVD expansion coefficients are rotated sets of principal component expansion coefficients. This way of thinking about SVD aids in the interpretation of results and provides guidance as to when and how to use SVD.Keywords
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