Principal Component and Correspondence Analyses Using R

Hervé Abdi is currently a full professor in the School of Behavioral and Brain Sciences at the University of Texas at Dallas and is the author or co-author of more than 250 publications (including 12 books). His recent work is concerned with face and person perception, odor perception, and with computational modeling of these processes. He is also developing statistical techniques to analyze the structure of large data sets as found, for example, in Genomics, brain imaging, and sensory evaluation (e.g., principal component analysis, correspondence analysis, Partial Least Square methods, STATIS, DISTATIS, discriminant correspondence analysis, multiple factor analysis, multi-table analysis, and additive tree representations). He is co-author (with Derek Beaton) of several R packages implementing these techniques. He teaches or has taught classes in cognition, computational modeling, experimental design, multivariate statistics, and the analysis of brain imaging data. Derek Beaton has a background in computer science and is currently working towards his PhD in Cognition and Neuroscience under his advisor, Dr. Hervé Abdi. Derek's interests are in developing new statistical approaches to better understand the contributions of genetics to brain and behavior. Recently, Derek was awarded a National Institutes of Health Ruth Kirschstein F31 fellowship via National Institute of Drug Abuse. His fellowship (co-sponsored by Drs. Hervé Abdi and Francesca Filbey) aims to reveal the genetic contributions to substance abuse and related traits. He is the main author of several R packages implementing the techniques described in this book.

Minimum of R.- Notations.- Principal Component Analysis.- Correspondence Analysis.- Multiple Correspondence Analysis & Alternative.- Appendix: The Singular Value Decomposition (SVD).- References.- Index.