Multivariate Regression – Techniques and Tools

Contents

• Cover
• Preface and Contents
  • Chapter 1: Introduction to Multivariate Modeling
  • Chapter 2: About Distributions
  • Chapter 3: Understanding Data
  • Chapter 4: “Quick and Dirty”
  • Chapter 5: Tackling with Redundancy
  • Chapter 6: Bridging Input and Output
  • Chapter 7: Towards the Structure
  • Chapter 8: Regression vs. Progression
  • Chapter 9: Application to Dynamic Models
  • Chapter 10: Relations to Systems Engineering
  • Chapter 11: Conclusion: About “Emergent Models”
• Bibliography: Bibliography
• Appendix A: Structure from Data
• Appendix A: Structure into Data
• Manual: Regression Toolbox Manual
• Toolbox: Regression Toolbox (zip-file)

Abstract

Multivariate statistical methods are powerful tools for analysis and manipulation of large data sets. This report introduces the most important statistical tools that can be used for multivariate regression in a general framework.

See the lecture slides on the course web page