Matrix Algebra Useful for Statistics 2/e [Searle] 9781118935149

This Second Edition addresses matrix algebra that is useful in the statistical analysis of data as well as within statistics as a whole. The material is presented in an explanatory style rather than a formal theorem-proof format and is self-contained. Featuring numerous applied illustrations, numerical examples, and exercises, the book has been updated to include the use of SAS, MATLAB, and R for the execution of matrix computations. In addition, André I. Khuri, who has extensive research and teaching experience in the field, joins this new edition as co-author. The Second Edition also:

• Contains new coverage on vector spaces and linear transformations and discusses computational aspects of matrices
• Covers the analysis of balanced linear models using direct products of matrices
• Analyzes multiresponse linear models where several responses can be of interest
• Includes extensive use of SAS, MATLAB, and R throughout
• Contains over 400 examples and exercises to reinforce understanding along with select solutions
• Includes plentiful new illustrations depicting the importance of geometry as well as historical interludes

Matrix Algebra Useful for Statistics, Second Edition is an ideal textbook for advanced undergraduate and first-year graduate level courses in statistics and other related disciplines. The book is also appropriate as a reference for independent readers who use statistics and wish to improve their knowledge of matrix algebra.

頁數：512
版次：第2版
年份：2017年
規格：精裝/單色
ISBN：9781118935149

PART I DEFINITIONS, BASIC CONCEPTS, AND MATRIX OPERATIONS
1 Vector Spaces, Subspaces, and Linear Transformations
2 Matrix Notation and Terminology
3 Determinants
4 Matrix Operations
5 Special Matrices
6 Eigenvalues and Eigenvectors
7 Diagonalization of Matrices
8 Generalized Inverses
9 Matrix Calculus
PART II APPLICATIONS OF MATRICES IN STATISTICS
10 Multivariate Distributions and Quadratic Forms
11 Matrix Algebra of Full-Rank Linear Models
12 Less-Than-Full-Rank Linear Models
13 Analysis of Balanced Linear Models Using Direct Products of Matrices
14 Multiresponse Models
PART III MATRIX COMPUTATIONS AND RELATED SOFTWARE
15 SAS/IML
16 Use of MATLAB in Matrix Computations
17 Use of R in Matrix Computations