| 书目名称 | Principal Component Analysis |
| 编辑 | I. T. Jolliffe |
| 视频video | |
| 丛书名称 | Springer Series in Statistics |
| 图书封面 |  |
| 描述 | 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 |
| 出版日期 | Book 2002Latest edition |
| 关键词 | Factor analysis; Regression analysis; principal component analysis; statistics; time series |
| 版次 | 2 |
| doi | https://doi.org/10.1007/b98835 |
| isbn_softcover | 978-1-4419-2999-0 |
| isbn_ebook | 978-0-387-22440-4Series ISSN 0172-7397 Series E-ISSN 2197-568X |
| issn_series | 0172-7397 |
| copyright | Springer Science+Business Media New York 2002 |
发表于 2025-3-21 16:20:13
