Description: This book offers a new method for studying hybrid models: Generalized Principal Component Analysis. Coverage includes statistical, geometric and algebraic concepts associated with estimation and segmentation of hybrid models, especially hybrid linear models.
Review Quotes: "The book under review provides a timely and comprehensive description of the classic and modern PCA-based and other dimension reduction techniques. Although the topic of dimension reduction has been briefly converted in quite a few books and review papers, this book should be especially applauded for its unique depth and comprehensiveness. ... Overall, this is one of the best books on PCA and modern dimension reduction techniques and should expect an increasing popularity." (Steven (Shuangge) Ma, Mathematical Reviews, January, 2017)