Matrix Algebra: Theory, Computations and Applications in Statistics
Second Edition
Springer, 2017
This book covers the theory of matrices and linear algebra for applications
in statistics. It also covers the basics of numerical analysis for computations
involving vectors and matrices.
The outline is
-
Preface
-
Table of Contents
- I. Linear Algebra
- 1. Basic Vector/Matrix Structure and Notation
- 2. Vectors and Vector Spaces
- 3. Basic Properties of Matrices
- 4. Vector/Matrix Derivatives and Integrals
- 5. Matrix Factorizations and Transformations
- 6. Solution of Linear Systems
- 7. Evaluation of Eigenvalues and Eigenvectors
- II. Applications in Data Analysis
- 8. Special Matrices and Operations Useful in Data Analysis
- 9. Selected Applications in Statistics
- III. Numerical Methods and Software
- 10. Numerical Methods
- 11. Numerical Linear Algebra
- 12. Software for Numerical Linear Algebra
- Bibliography
-
Subject Index
Errata.
I would appreciate
any feedback from readers -- corrections, suggestions, or general
comments.
Errata for first edition.
James Gentle, jgentle@gmu.edu