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Matrix Tricks for Linear Statistical Models

Our Personal Top Twenty

  • Simo Puntanen
  • George P. H. Styan
  • Jarkko Isotalo

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 1-56
  3. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 57-70
  4. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 71-90
  5. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 91-104
  6. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 105-120
  7. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 121-144
  8. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 145-150
  9. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 151-154
  10. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 155-190
  11. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 191-214
  12. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 215-266
  13. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 267-282
  14. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 283-290
  15. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 291-304
  16. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 305-316
  17. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 317-342
  18. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 343-348
  19. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 349-356
  20. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 357-390
  21. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 391-414
  22. Simo Puntanen, George P. H. Styan, Jarkko Isotalo
    Pages 415-426
  23. Back Matter
    Pages 427-486

About this book

Introduction

In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple “tricks” which simplify and clarify the treatment of a problem—both for the student and for the professor. Of course, the concept of a trick is not uniquely defined—by a trick we simply mean here a useful important handy result.
In this book we collect together our Top Twenty favourite matrix tricks for linear statistical models.

Keywords

Löwner ordering Schur complement best linear unbiased estimation generalized inverse orthogonal projector singular value decomposition

Authors and affiliations

  • Simo Puntanen
    • 1
  • George P. H. Styan
    • 2
  • Jarkko Isotalo
    • 3
  1. 1.Dept. Mathematics, Statistics &, PhilosophyUniversity of TampereTampereFinland
  2. 2.Dept. Mathematics & StatisticsMcGill UniversityMontrealCanada
  3. 3.Dept. Mathematics, Statistics &, PhilosophyUniversity of TampereTampereFinland

Bibliographic information