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RT Book, Whole SR Electronic DC OPAC T1 Principal Component Analysis / by I. T. Jolliffe T2 Springer Series in Statistics A1 Jolliffe, I. T. A1 SpringerLink (Online service) YR 2002 FD 2002 SP XXX, 488 p K1 Statistics K1 Statistics K1 Statistical Theory and Methods ED Second Edition PB Springer New York PP New York, NY SN 9780387224404 LA English (英語) CL DC23:519.5 NO Principal component analysis is central to the study of multivariate data. Although one of the earliest multivariate techniques, it continues to be the subject of much research, ranging from new model-based approaches to algorithmic ideas from neural networks. It is extremely versatile, with applications in many disciplines. The first edition of this book was the first comprehensive text written solely on principal component analysis. The second edition updates and substantially expands the original version, and is once again the definitive text on the subject. It includes core material, current research and a wide range of applications. Its length is nearly double that of the first edition. Researchers in statistics, or in other fields that use principal component analysis, will find that the book gives an authoritative yet accessible account of the subject. It is also a valuable resource for graduate courses in multivariate analysis. The book requires some knowledge of matrix algebra. Ian Jolliffe is Professor of Statistics at the University of Aberdeen. He is author or co-author of over 60 research papers and three other books. His research interests are broad, but aspects of principal component analysis have fascinated him and kept him busy for over 30 years NO 書誌ID=1002989065; LK [E Book]http://dx.doi.org/10.1007/b98835 OL 30