Principal component analysis / I.T. Jolliffe
- 作者： Jolliffe, I. T.
- 其他作者：
- 其他題名：
- Springer e-books
- 出版： New York : Springer c2002
- 叢書名： Springer series in statistics
- 主題： Principal components analysis.
- 版本：2nd ed.
- ISBN： 9780387224404 (electronic bk.) 、 9780387954424 (paper)
- URL：
電子書
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讀者標籤：
- 系統號： 005168859 | 機讀編目格式
館藏資訊
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.