Constrained Principal Component Analysis and Related Techniques

Constrained Principal Component Analysis and Related Techniques begins with four concrete examples of constrained principal component analysis (CPCA) that provide readers with a basic understanding of the technique and its applications. It gives a detailed account of two key mathematical ideas in CPCA: projection and singular value decomposition. The author then describes the basic data requirements, models, and analytical tools for CPCA and their immediate extensions. He also introduces techniques that are special cases of, or closely related to, CPCA and discusses several topics relevant to practical uses of CPCA. The book concludes with a technique that imposes different constraints on different dimensions (DCDD), along with its analytical extensions.

MATLAB programs for CPCA and DCDD as well as data to create the book’s examples are available on the author’s website.