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Reduced Rank Regression

With Applications to Quantitative Structure-Activity Relationships

  • Book
  • © 1995

Overview

Authors:
  1. Heinz Schmidli

    1. Mathematical Applications, CIBA-GEIGY Ltd., Basel, Switzerland

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Part of the book series: Contributions to Statistics (CONTRIB.STAT.)

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-x
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  2. Introduction

    • Heinz Schmidli
    Pages 1-4

  3. Quantitative Structure Activity Relationships (QSAR)

    • Heinz Schmidli
    Pages 5-15

  4. Linear Multivariate Prediction

    • Heinz Schmidli
    Pages 16-37

  5. Heuristic Multivariate Prediction Methods

    • Heinz Schmidli
    Pages 38-48

  6. Classical Analysis of Reduced Rank Regression

    • Heinz Schmidli
    Pages 49-102

  7. Bayesian Analysis of Reduced Rank Regression

    • Heinz Schmidli
    Pages 103-127

  8. Case Studies

    • Heinz Schmidli
    Pages 128-151

  9. Discussion

    • Heinz Schmidli
    Pages 152-165

  10. Back Matter

    Pages 167-179
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Keywords

About this 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).

Authors and Affiliations

  • Mathematical Applications, CIBA-GEIGY Ltd., Basel, Switzerland

    Heinz Schmidli

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