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Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: Linear algebra and the study of matrix algorithms have become fundamental to the development of statistical models. Using a vector space approach, this book provides an understanding of the major concepts that underlie linear algebra and matrix analysis. Each chapter introduces a key topic such as infinite-dimensional spaces and provides illustrative examples. The author examines recent developments in diverse fields such as spatial statistics, machine learning, data mining and social network analysis. Complete in its coverage and accessible to students without prior knowledge of linear algebra, the text also includes results that are useful for traditional statistical applications. Bookseller Inventory #

**Synopsis:**

**Linear Algebra and Matrix Analysis for Statistics** offers a gradual exposition to linear algebra without sacrificing the rigor of the subject. It presents both the vector space approach and the canonical forms in matrix theory. The book is as self-contained as possible, assuming no prior knowledge of linear algebra.

The authors first address the rudimentary mechanics of linear systems using Gaussian elimination and the resulting decompositions. They introduce Euclidean vector spaces using less abstract concepts and make connections to systems of linear equations wherever possible. After illustrating the importance of the rank of a matrix, they discuss complementary subspaces, oblique projectors, orthogonality, orthogonal projections and projectors, and orthogonal reduction.

The text then shows how the theoretical concepts developed are handy in analyzing solutions for linear systems. The authors also explain how determinants are useful for characterizing and deriving properties concerning matrices and linear systems. They then cover eigenvalues, eigenvectors, singular value decomposition, Jordan decomposition (including a proof), quadratic forms, and Kronecker and Hadamard products. The book concludes with accessible treatments of advanced topics, such as linear iterative systems, convergence of matrices, more general vector spaces, linear transformations, and Hilbert spaces.

**About the Author:**
University of Minnesota, Minneapolis, USA Department of Math and Statistics, University of Maryland Baltimore County, USA

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**Book Description **Chapman and Hall/CRC, 2014. HRD. Book Condition: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Bookseller Inventory # GB-9781420095388

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Taylor and Francis 2014-06-03, Boca Raton
(2014)

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**Book Description **Taylor and Francis 2014-06-03, Boca Raton, 2014. hardback. Book Condition: New. Bookseller Inventory # 9781420095388

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Chapman and Hall/CRC 2014-07-08
(2014)

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**Book Description **Chapman and Hall/CRC 2014-07-08, 2014. Book Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely. Bookseller Inventory # NU-GRD-05295909

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Taylor Francis Ltd, United States
(2014)

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**Book Description **Taylor Francis Ltd, United States, 2014. Hardback. Book Condition: New. Language: English . Brand New Book. Linear Algebra and Matrix Analysis for Statistics offers a gradual exposition to linear algebra without sacrificing the rigor of the subject. It presents both the vector space approach and the canonical forms in matrix theory. The book is as self-contained as possible, assuming no prior knowledge of linear algebra. The authors first address the rudimentary mechanics of linear systems using Gaussian elimination and the resulting decompositions. They introduce Euclidean vector spaces using less abstract concepts and make connections to systems of linear equations wherever possible. After illustrating the importance of the rank of a matrix, they discuss complementary subspaces, oblique projectors, orthogonality, orthogonal projections and projectors, and orthogonal reduction. The text then shows how the theoretical concepts developed are handy in analyzing solutions for linear systems. The authors also explain how determinants are useful for characterizing and deriving properties concerning matrices and linear systems. They then cover eigenvalues, eigenvectors, singular value decomposition, Jordan decomposition (including a proof), quadratic forms, and Kronecker and Hadamard products. The book concludes with accessible treatments of advanced topics, such as linear iterative systems, convergence of matrices, more general vector spaces, linear transformations, and Hilbert spaces. Bookseller Inventory # AA69781420095388

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ISBN 10: 1420095382
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**Book Description **Book Condition: New. Bookseller Inventory # ST1420095382. Bookseller Inventory # ST1420095382

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Published by
Taylor Francis Ltd, United States
(2014)

ISBN 10: 1420095382
ISBN 13: 9781420095388

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**Book Description **Taylor Francis Ltd, United States, 2014. Hardback. Book Condition: New. Language: English . Brand New Book. Linear Algebra and Matrix Analysis for Statistics offers a gradual exposition to linear algebra without sacrificing the rigor of the subject. It presents both the vector space approach and the canonical forms in matrix theory. The book is as self-contained as possible, assuming no prior knowledge of linear algebra. The authors first address the rudimentary mechanics of linear systems using Gaussian elimination and the resulting decompositions. They introduce Euclidean vector spaces using less abstract concepts and make connections to systems of linear equations wherever possible. After illustrating the importance of the rank of a matrix, they discuss complementary subspaces, oblique projectors, orthogonality, orthogonal projections and projectors, and orthogonal reduction. The text then shows how the theoretical concepts developed are handy in analyzing solutions for linear systems. The authors also explain how determinants are useful for characterizing and deriving properties concerning matrices and linear systems. They then cover eigenvalues, eigenvectors, singular value decomposition, Jordan decomposition (including a proof), quadratic forms, and Kronecker and Hadamard products. The book concludes with accessible treatments of advanced topics, such as linear iterative systems, convergence of matrices, more general vector spaces, linear transformations, and Hilbert spaces. Bookseller Inventory # AA69781420095388

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Taylor and Francis
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**Book Description **Taylor and Francis, 2014. HRD. Book Condition: New. New Book. Shipped from US within 10 to 14 business days. Established seller since 2000. Bookseller Inventory # VT-9781420095388

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**Book Description **Chapman and Hall/CRC, 2014. Hardback. Book Condition: NEW. 9781420095388 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Bookseller Inventory # HTANDREE0724057

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Published by
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**Book Description **Chapman and Hall/CRC, 2014. Book Condition: New. book. Bookseller Inventory # ria9781420095388_rkm

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