Matrix Algebra Useful for Statistics. Wiley Series in Probability and Statistics

  • ID: 2169251
  • Book
  • 476 Pages
  • John Wiley and Sons Ltd
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The Wiley–Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.

"This book is intended to teach useful matrix algebra to ′students, teachers, consultants, researchers, and practitioners′ in ′statistics and other quantitative methods′.The author concentrates on practical matters, and writes in a friendly and informal style . . . this is a useful and enjoyable book to have at hand."

This book is an easy–to–understand guide to matrix algebra and its uses in statistical analysis. The material is presented in an explanatory style rather than the formal theorem–proof format. This self–contained text includes numerous applied illustrations, numerical examples, and exercises.

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1. Introduction.

2. Basic Operations.

3. Special Matrices.

4. Determinants.

5. Inverse Matrices.

6. Rank.

7. Canonical Forms.

8. Generalized Inverses.

9. Solving Linear Equations.

10. Partitioned Matrices.

11. Eigenvalues and Eigenvectors.

11A. Appendix to Chapter 11.

12. Miscellanea.

13. Applications in Statistics.

14. The Matrix Algebra of Regression Analysis.

15. An Introduction to Linear Statistical Models.



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SHAYLE R. SEARLE, PhD, is Professor Emeritus of Biometry at Cornell University. He is the author of Linear Models, Linear Models for Unbalanced Data, and Generalized, Linear, and Mixed Models (with Charles E. McCulloch), all from Wiley.
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