Matrix Algebra for Linear Models
eBook - ePub

Matrix Algebra for Linear Models

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Matrix Algebra for Linear Models

About this book

A self-contained introduction to matrix analysis theory and applications in the field of statistics

Comprehensive in scope, Matrix Algebra for Linear Models offers a succinct summary of matrix theory and its related applications to statistics, especially linear models. The book provides a unified presentation of the mathematical properties and statistical applications of matrices in order to define and manipulate data.

Written for theoretical and applied statisticians, the book utilizes multiple numerical examples to illustrate key ideas, methods, and techniques crucial to understanding matrix algebra's application in linear models. Matrix Algebra for Linear Models expertly balances concepts and methods allowing for a side-by-side presentation of matrix theory and its linear model applications. Including concise summaries on each topic, the book also features:

  • Methods of deriving results from the properties of eigenvalues and the singular value decomposition
  • Solutions to matrix optimization problems for obtaining more efficient biased estimators for parameters in linear regression models
  • A section on the generalized singular value decomposition
  • Multiple chapter exercises with selected answers to enhance understanding of the presented material

Matrix Algebra for Linear Models is an ideal textbook for advanced undergraduate and graduate-level courses on statistics, matrices, and linear algebra. The book is also an excellent reference for statisticians, engineers, economists, and readers interested in the linear statistical model.

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Yes, you can access Matrix Algebra for Linear Models by Marvin H. J. Gruber in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley
Year
2013
Print ISBN
9781118592557
eBook ISBN
9781118608814
Edition
1
Topic
Mathematics
Subtopic
Probability & Statistics
Index
Mathematics

Table of contents

  1. COVER
  2. TITLE PAGE
  3. COPYRIGHT PAGE
  4. DEDICATION
  5. PREFACE
  6. ACKNOWLEDGMENTS
  7. PART I: BASIC IDEAS ABOUT MATRICES AND SYSTEMS OF LINEAR EQUATIONS
  8. PART II: EIGENVALUES, THE SINGULAR VALUE DECOMPOSITION, AND PRINCIPAL COMPONENTS
  9. PART III: GENERALIZED INVERSES
  10. PART IV: QUADRATIC FORMS AND THE ANALYSIS OF VARIANCE
  11. PART V: MATRIX OPTIMIZATION PROBLEMS
  12. ANSWERS TO SELECTED EXERCISES
  13. REFERENCES
  14. INDEX