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Matrix Algebra From a Statistician’s Perspective

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Cover of 'Matrix Algebra From a Statistician’s Perspective'

Table of Contents

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    Book Overview
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    Chapter 1 Matrices
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    Chapter 2 Submatrices and Partitioned Matrices
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    Chapter 3 Linear Dependence and Independence
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    Chapter 4 Linear Spaces: Row and Column Spaces
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    Chapter 5 Trace of a (Square) Matrix
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    Chapter 6 Geometrical Considerations
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    Chapter 7 Linear Systems: Consistency and Compatibility
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    Chapter 8 Inverse Matrices
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    Chapter 9 Generalized Inverses
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    Chapter 10 Idempotent Matrices
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    Chapter 11 Linear Systems: Solutions
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    Chapter 12 Projections and Projection Matrices
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    Chapter 13 Determinants
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    Chapter 14 Linear, Bilinear, and Quadratic Forms
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    Chapter 15 Matrix Differentiation
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    Chapter 16 Kronecker Products and the Vec and Vech Operators
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    Chapter 17 Intersections and Sums of Subspaces
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    Chapter 18 Sums (and Differences) of Matrices
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    Chapter 19 Minimization of a Second-Degree Polynomial (in n Variables) Subject to Linear Constraints
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    Chapter 20 The Moore-Penrose Inverse
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    Chapter 21 Eigenvalues and Eigenvectors
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    Chapter 22 Linear Transformations
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    Chapter 23 Erratum
Attention for Chapter 21: Eigenvalues and Eigenvectors
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