article · 2007

Principal Component Analysis

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Abstract

Introduction The Karhunen-Lo`eve basis functions, more frequently referred to as principal components or empirical orthogonal functions (EOFs), of the noise response of the climate system are an important tool for geophysical studies. Many researchers have used this tool to examine the geophysical and climatological phenomena. Perhaps more frequent use of EOFs in recent studies is in conjunction with the development of the signal detection and estimation methods (e.g., Barnett et al. 1991; Hasselmann 1993; Hegerl et al. 1994; Santer et al. 1994; Shen et al. 1994; North et al. 1995; North and Kim 1995; Kim et al. 1996c). In such studies, the frequencydependent EOFs (fdEOFs; Wallace and Dickinson 1972; North 1984; Hasselmann 1988; Kim and North 1993) of the background fluctuations of a detection variable serve as an orthogonal basis set and are used to design optimal techniques for detecting and estimating signals. A detection and prediction approach is to design a filter or opti

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APA 7

? (2007). Principal Component Analysis.

MLA 9

? “Principal Component Analysis.” 2007.

Chicago

? 2007. “Principal Component Analysis.”

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? (2007) ‘Principal Component Analysis’.

BibTeX

@article{anon2007principal,
  title = {{Principal Component Analysis}},
  author = {?},
  year = {2007}
}

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