Matrix Algebra Useful for Statistics, 2/e (Hardcover)
暫譯: 統計學中有用的矩陣代數（第二版）

Shayle R. Searle , Andre I. Khuri

Matrix Algebra Useful for Statistics, 2/e (Hardcover)

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本書序言

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. 

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.

本書特色

●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

商品描述(中文翻譯)

本書序言

本書的第二版探討了在數據統計分析中有用的矩陣代數，以及在整個統計學中的應用。材料以解釋性風格呈現，而非正式的定理-證明格式，並且是自足的。書中包含了大量的應用插圖、數值範例和練習，並更新了使用SAS、MATLAB和R進行矩陣計算的內容。此外，擁有豐富研究和教學經驗的André I. Khuri作為共同作者參與了這一新版的編寫。

對統計學有用的矩陣代數，第二版是高年級本科生和研究生一年級統計學及其他相關學科課程的理想教科書。本書也適合作為獨立讀者的參考，特別是那些使用統計並希望提高其矩陣代數知識的人。

本書特色

● 包含有關向量空間和線性變換的新內容，並討論矩陣的計算方面

● 涵蓋使用矩陣的直接乘積分析平衡線性模型

● 分析多響應線性模型，其中多個響應可能是感興趣的對象

● 全書廣泛使用SAS、MATLAB和R

● 包含超過400個範例和練習，以加強理解，並附有選擇性解答

● 包含大量新插圖，展示幾何的重要性以及歷史插曲

目錄大綱

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

目錄大綱(中文翻譯)

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

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