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September 1, 1998Biometrics676 citationsOpen Access

Matrix Algebra From a Statistician's Perspective.

DHDavid A. Harville

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Abstract

Preface. - Matrices. - Submatrices and partitioned matricies. - Linear dependence and independence. - Linear spaces: row and column spaces. - Trace of a (square) matrix. - Geometrical considerations. - Linear systems: consistency and compatability. - Inverse matrices. - Generalized inverses. - Indepotent matrices. - Linear systems: solutions. - Projections and projection matrices. - Determinants. - Linear, bilinear, and quadratic forms. - Matrix differentiation. - Kronecker products and the vec and vech operators. - Intersections and sums of subspaces. - Sums (and differences) of matrices. - Minimzation of a second-degree polynomial (in n variables) subject to linear constraints. - The Moore-Penrose inverse. - Eigenvalues and Eigenvectors. - Linear transformations. - References. - Index.

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David A. Harville (1998) studied this question.

synapsesocial.com/papers/6a6f9d30660549caf2c425cdhttps://doi.org/10.2307/2533884
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