Author Description

This book provides an account of the theory and applications of multivariate reduced-rank regression, a tool of multivariate analysis that recently has come into increased use in broad areas of applications. In addition to a historical review of the topic, its connection to other widely used statistical methods - such as multivariate analysis of variance (MANOVA), discriminant analysis, principal components, canonical correlation analysis, and errors-in-variables models - is also discussed. This book should appeal to both practitioners and researchers who may deal with moderate and high-dimensional multivariate data. This book can be ideally used for seminar-type courses taken by advanced graduate students in statistics, econometrics, business, and engineering.