Matrix algebra from a statistician's perspective / David A. Harville.
By: Harville, David A.
Material type: BookPublisher: New York : Springer, c1997Description: xvii, 630 p. : ill. ; 24 cm. + hbk.ISBN: 038794978X.Subject(s): Algebras, Linear | Linear models (Statistics)DDC classification: 512.5Item type | Current library | Call number | Copy number | Status | Date due | Barcode | Item holds |
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General Lending | MTU Bishopstown Library Lending | 512.5 (Browse shelf(Opens below)) | 1 | Available | 00074767 |
Enhanced descriptions from Syndetics:
A knowledge of matrix algebra is a prerequisite for the study of much of modern statistics, especially the areas of linear statistical models and multivariate statistics. This reference book provides the background in matrix algebra necessary to do research and understand the results in these areas. Essentially self-contained, the book is best-suited for a reader who has had some previous exposure to matrices. Solultions to the exercises are available in the author's "Matrix Algebra: Exercises and Solutions."
Includes bibliographical references (pages 615-618) and index.
Matrices -- Submatrices and partitioned matrices -- Linear dependence and independence -- Linear spaces: row and column spaces -- Trace of a (square) matrix -- Geometrical considerations -- Linear systems: consistency and compatibility -- Inverse matrices -- Generalized inverses -- Idempotent 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 -- Minimization of a second- degree polynomial (in n variables) subject to linear constraints -- The Moore-Penrose inverse -- Eigenvalues and Eigenvectors -- Linear transformations.