Constrained Principal Component Analysis and Related Techniques
1st Edition
Published on 19. April 2016
251 pages
978-1-4665-5668-3 (ISBN)
Description
In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? Why and when is it a good idea to combine them? Wha
Reviews / Votes
"Takane is a renowned worker in this field and he draws upon his vast array of papers in the area to write an extremely informative review of the subject. ... To bring together all the topics contained in the book, and to present them in such a clear and concise manner, is a great achievement. The author's aim of promoting principal component analysis as more than just an exploratory data analysis tool has been achieved. ... For those interested in the topic, the book is worth purchasing. It would be a useful addition to any library. I wholeheartedly recommend this book."-Journal of Applied Statistics, 2014
"Coverage of principal component analysis (PCA) in books ranges from chapters to entire texts. ... None of these books nor this line of research, however, describes PCA from the perspective of this text. ...Though emphasizing algebra, Takane provides numerous examples that illustrate the methodology."
-Robert A. Stine, Journal of the American Statistical Association, September 2014, Vol. 109
More details
Series
Language
English
Place of publication
Philadelphia, PA
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Statisticians, psychometricians, and biometricians; researchers in machine learning, computer image processing, and engineering; graduate students in statistics.
Illustrations
14 s/w Abbildungen, 18 s/w Tabellen
14 b/w images and 18 tables
File size
2,92 MB
ISBN-13
978-1-4665-5668-3 (9781466556683)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
06/2020
1st Edition
Chapman & Hall/CRC
€73.50
Shipment within 15-20 days
Book
10/2013
1st Edition
CRC Press
€148.79
Shipment within 15-20 days
Person
Yoshio Takane is an emeritus professor at McGill University and an adjunct professor at the University of Victoria. He is a former president of the Psychometric Society and a recipient of a Career Award from the Behaviormetric Society of Japan and a Special Award from the Japanese Psychological Association. His recent interests include regularization techniques for multivariate data analysis, acceleration methods for iterative model fitting, the development of structural equation models for analyzing brain connectivity, and various kinds of singular value decompositions. He earned his DL from the University of Tokyo and PhD from the University of North Carolina at Chapel Hill.
Content
Introduction. Mathematical Foundation. Constrained Principal Component Analysis (CPCA). Special Cases and Related Methods. Related Topics of Interest. Different Constraints on Different Dimensions (DCDD). Epilogue. Appendix. Bibliography. Index.
