《矩陣代數》是2017年5月1日世界圖書出版公司出版的著作，作者是[美] J.E.金特爾。
基本介紹
- 中文名：《矩陣代數》
- 作者：[美] J.E.金特爾
- 出版社：世界圖書出版公司
- 出版時間：2017年05月01日
- 定價：99 元
- 開本：16 開
- 裝幀：平裝-膠訂
- ISBN：9787519219697
內容簡介,目錄,
內容簡介
矩陣代數是用於數據分析和統計領域的重要數學理論。本書《矩陣代數》是一部教科書，第一部分提供了照迎潤在統計學中套用的矩陣代數理論，第2部分主要講套用，第3部分論及數值線性代數。本書各章有大量習題，書後附錄有題解或提示。朽翻照組尋紋可作為統計專業的矩陣代棕碑道數教材。讀辨詢估者對象：數汗刪熱理統計專業榆歸敬盼的學生教材。
目錄
Preface
Part Ⅰ Linear Algebra
1 Basic Vector/Matrix Structure and Notation
1.1 Vectors
1.2 Arrays
1.3 Matrices
1.4 Representation of Data
2 Vectors and Vector Spaces
2.1 Operations on Vectors
2.1.1 Linear Combinations and Linear Independence
2.1.2 Vector Spaces and Spaces of Vectors
2.1.3 Basis Sets
2.1.4 Inner Products
2.1.5 Norms
2.1.6 Normalized Vectors
2.1.7 Metrics and Distances
2.1.8 Orthogonal Vectors and Orthogonal Vector Spaces
2.1.9 The "One Vector"
2.2 Cartesian Coordinates and Geometrical Properties of Vectors
2.2.1 Cartesian Geometry
2.2.2 Projections
2.2.3 Angles between Vectors
2.2.4 Orthogonalization：Transformations
2.2.5 Orthonormal Basis Sets
2.2.6 Approximation of Vectors
2.2.7 Flats， Affine Spaces， and Hyperplanes
2.2.8 Cones
2.2.9 Cross Products in IR3
2.3 Centered Vectors and Variances and Covariances of Vectors
2.3.1 The Mean and Centered Vectors
2.3.2 The Standard Deviation， the Variance， and Scaled Vectors
2.3.3 Covariances and Correlations between Vectors
Exercises
3 Basic Properties of Matrices
3.1 Basic Definitions and Notation
3.1.1 Matrix Shaping Operators
3.1.2 Partitioned Matrices
3.1.3 Matrix Addition
3.1.4 Scalar—Valued Operators on Square Matrices： The Trace
3.1.5 Scalar—Valued Operators on Square Matrices： The Determinant
3.2 Multiplication of Matrices and Multiplication of Vectors and Matrices
3.2.1 Matrix Multiplication （Cayley）
3.2.2 Multiplication of Partitioned Matrices
3.2.3 Elementary Operations on Matrices
3.2.4 Traces and Determinants of Square Cayley Products
3.2.5 Multiplication of Matrices and Vectors
3.2.6 Outer Products
3.2.7 Bilinear and Quadratic Forms； Definiteness
3.2.8 Anisometric Spaces
3.2.9 Other Kinds of Matrix Multiplication
3.3 Matrix Rank and the Inverse of a Full Rank Matrix
3.3.1 The Rank of Partitioned Matrices， Products of Matrices， and Sums of Matrices
3.3.2 Full Rank Partitioning
3.3.3 Full Rank Matrices and Matrix Inverses
3.3.4 Full Rank Factorization
3.3.5 Equivalent Matrices
3.3.6 Multiplication by Full Rank Matrices
3.3.7 Products of the Form ATA
3.3.8 A Lower Bound on the Rank of a Matrix Product
3.3.9 Determinants of Inverses
3.3.10 Inverses of Products and Sums of Matrices
3.3.11 Inverses of Matrices with Special Forms
3.3.12 Determining the Rank of a Matrix
3.4 More on Partitioned Square Matrices： The Schur Complement
3.4.1 Inverses of Partitioned Matrices
3.4.2 Determinants of Partitioned Matrices
……
Part Ⅱ Applications in Data Analysis
Part Ⅲ Numerical Methods and Software
A Notation and Definitions
B Solutions and Hints for Selected Exercises
Bibliography
Index
2.3.2 The Standard Deviation， the Variance， and Scaled Vectors
2.3.3 Covariances and Correlations between Vectors
Exercises
3 Basic Properties of Matrices
3.1 Basic Definitions and Notation
3.1.1 Matrix Shaping Operators
3.1.2 Partitioned Matrices
3.1.3 Matrix Addition
3.1.4 Scalar—Valued Operators on Square Matrices： The Trace
3.1.5 Scalar—Valued Operators on Square Matrices： The Determinant
3.2 Multiplication of Matrices and Multiplication of Vectors and Matrices
3.2.1 Matrix Multiplication （Cayley）
3.2.2 Multiplication of Partitioned Matrices
3.2.3 Elementary Operations on Matrices
3.2.4 Traces and Determinants of Square Cayley Products
3.2.5 Multiplication of Matrices and Vectors
3.2.6 Outer Products
3.2.7 Bilinear and Quadratic Forms； Definiteness
3.2.8 Anisometric Spaces
3.2.9 Other Kinds of Matrix Multiplication
3.3 Matrix Rank and the Inverse of a Full Rank Matrix
3.3.1 The Rank of Partitioned Matrices， Products of Matrices， and Sums of Matrices
3.3.2 Full Rank Partitioning
3.3.3 Full Rank Matrices and Matrix Inverses
3.3.4 Full Rank Factorization
3.3.5 Equivalent Matrices
3.3.6 Multiplication by Full Rank Matrices
3.3.7 Products of the Form ATA
3.3.8 A Lower Bound on the Rank of a Matrix Product
3.3.9 Determinants of Inverses
3.3.10 Inverses of Products and Sums of Matrices
3.3.11 Inverses of Matrices with Special Forms
3.3.12 Determining the Rank of a Matrix
3.4 More on Partitioned Square Matrices： The Schur Complement
3.4.1 Inverses of Partitioned Matrices
3.4.2 Determinants of Partitioned Matrices
……
Part Ⅱ Applications in Data Analysis
Part Ⅲ Numerical Methods and Software
A Notation and Definitions
B Solutions and Hints for Selected Exercises
Bibliography
Index
