Reduced rank regression : with applications to quantitative structure-activity relationships /
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 i...
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| Format: | eBook |
| Language: | English |
| Published: |
Heidelberg :
Physica-Verlag,
[1995]
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| Series: | Contributions to statistics.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | 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). |
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| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (x, 179 pages) : illustrations. |
| Format: | Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. |
| Bibliography: | Includes bibliographical references (pages [167]-174) and index. |
| ISBN: | 9783642500152 (electronic bk.) 3642500153 (electronic bk.) |