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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
University of Minnesota, Minneapolis, USA Department of Math and Statistics, University of Maryland Baltimore County, USA
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : HPB-Red, Dallas, TX, Etats-Unis
Hardcover. Etat : Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! N° de réf. du vendeur S_418634690
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 6752058-n
Quantité disponible : Plus de 20 disponibles
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Mar2411530197937
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 6752058
Quantité disponible : Plus de 20 disponibles
Vendeur : Chiron Media, Wallingford, Royaume-Uni
Hardcover. Etat : New. N° de réf. du vendeur 6666-TNFPD-9781420095388
Quantité disponible : 5 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 6752058-n
Quantité disponible : Plus de 20 disponibles
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. pp. 580 12 Illus. This item is printed on demand. N° de réf. du vendeur 6751335
Quantité disponible : 3 disponible(s)
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9781420095388
Quantité disponible : Plus de 20 disponibles
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 582 pp. Englisch. N° de réf. du vendeur 9781420095388
Quantité disponible : 2 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 6752058
Quantité disponible : Plus de 20 disponibles