Principal Component Analysis

I. T. Jolliffe

ISBN 10: 1441929991 / ISBN 13: 9781441929990

Published by Springer New York, Springer New York Dez 2010, 2010

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -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. 524 pp. Englisch.

Seller Inventory # 9781441929990

Bibliographic Details

• Title: Principal Component Analysis
• Publisher: Springer New York, Springer New York Dez 2010
• Publication Date: 2010
• Language: English
• ISBN 10: 1441929991
• ISBN 13: 9781441929990
• Binding: Taschenbuch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 235W x 155H x 29D millimeters 235 millimeters width by 155 millimeters height by 29 millimeters depth
• Weight: 785 grams

About this title

Synopsis

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.

About the Author

I. T. Jolliffe is Professor of Statistics at the University of Aberdeen.