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Reduced rank regression

Heinz Schmidli · 1995

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About the book

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).

Book details

Year
1995
Language
English
Publisher
Physica-Verlag
Editions
2
ISBN
9783642500152

Data source: Wikidata