Schmidli D. Reduced Rank Regression

Heldelberg: Springer, 1995. - 179p.Reduced rank regression is widely used in statistics to model multivariate data. In this monograph, theoretical and data analytical approaches are developed for the application of reduced rank regression in multivariate prediction problems. For the first time, both classical and Bayesian inference is discussed, using recently proposed procedures such as the ECM-algorithm and the Gibbs sampler. All methods are motivated and illustrated by examples taken from the area of quantitative structure-activity relationships (QSAR).Quantitative Structure Activity Relationships (QSAR)
Linear Multivariate Prediction
Heuristic Multivariate Prediction Methods
Classical Analysis of Reduced Rank Regression
Bayesian Analysis of Reduced Rank Regression
Case Studies
Discussion