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.
机构:
Sao Paulo State Univ UNESP, Dept Phys, IBILCE, BR-15054000 Sao Jose Do Rio Preto, SP, BrazilSao Paulo State Univ UNESP, Dept Phys, IBILCE, BR-15054000 Sao Jose Do Rio Preto, SP, Brazil
Galo, Andre Luiz
Colombo, Marcio Francisco
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Sao Paulo State Univ UNESP, Dept Phys, IBILCE, BR-15054000 Sao Jose Do Rio Preto, SP, BrazilSao Paulo State Univ UNESP, Dept Phys, IBILCE, BR-15054000 Sao Jose Do Rio Preto, SP, Brazil
机构:
S China Normal Univ, Sch Math Sci, Guangzhou 510631, Guangdong, Peoples R ChinaS China Normal Univ, Sch Math Sci, Guangzhou 510631, Guangdong, Peoples R China
Chen, Xiao Shan
Li, Wen
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S China Normal Univ, Sch Math Sci, Guangzhou 510631, Guangdong, Peoples R ChinaS China Normal Univ, Sch Math Sci, Guangzhou 510631, Guangdong, Peoples R China