„This book maintains its uniqueness among the competition throughits extensive referencing to proofs and comprehensive coverage oftopics not found in any other one book.“ (InternationalStatistical Review, December 2008)
„This book maintains its uniqueness among the competitionthrough its extensive referencing to proofs and comprehensivecoverage of topics not found in any other one book.“(International Statistical Review, Dec 2008)
„This is an authoritative and comprehensive reference that willbe useful to researchers who need to use the results of matrixanalysis in their work. It would also be a useful addition to thereference collection of any mathematical library.“ (MAAReview, March 2008)
A Matrix Handbook for Statisticians
von George A. F. SeberA comprehensive, must-have handbook of matrix methods with a uniqueemphasis on statistical applications
This timely book, A Matrix Handbook for Statisticians, providesa comprehensive, encyclopedic treatment of matrices as they relateto both statistical concepts and methodologies. Written by anexperienced authority on matrices and statistical theory, thishandbook is organized by topic rather than mathematicaldevelopments and includes numerous references to both the theorybehind the methods and the applications of the methods. A uniformapproach is applied to each chapter, which contains four parts: adefinition followed by a list of results; a short list ofreferences to related topics in the book; one or more references toproofs; and references to applications. The use of extensivecross-referencing to topics within the book and externalreferencing to proofs allows for definitions to be located easilyas well as interrelationships among subject areas to berecognized.
A Matrix Handbook for Statisticians addresses the need formatrix theory topics to be presented together in one book andfeatures a collection of topics not found elsewhere under onecover. These topics include:
* Complex matrices
* A wide range of special matrices and their properties
* Special products and operators, such as the Kroneckerproduct
* Partitioned and patterned matrices
* Matrix analysis and approximation
* Matrix optimization
* Majorization
* Random vectors and matrices
* Inequalities, such as probabilistic inequalities
Additional topics, such as rank, eigenvalues, determinants, norms, generalized inverses, linear and quadratic equations, differentiation, and Jacobians, are also included. The book assumesa fundamental knowledge of vectors and matrices, maintains areasonable level of abstraction when appropriate, and provides acomprehensive compendium of linear algebra results with use orpotential use in statistics. A Matrix Handbook for Statisticians isan essential, one-of-a-kind book for graduate-level courses inadvanced statistical studies including linear and nonlinear models, multivariate analysis, and statistical computing. It also serves asan excellent self-study guide for statistical researchers.
This timely book, A Matrix Handbook for Statisticians, providesa comprehensive, encyclopedic treatment of matrices as they relateto both statistical concepts and methodologies. Written by anexperienced authority on matrices and statistical theory, thishandbook is organized by topic rather than mathematicaldevelopments and includes numerous references to both the theorybehind the methods and the applications of the methods. A uniformapproach is applied to each chapter, which contains four parts: adefinition followed by a list of results; a short list ofreferences to related topics in the book; one or more references toproofs; and references to applications. The use of extensivecross-referencing to topics within the book and externalreferencing to proofs allows for definitions to be located easilyas well as interrelationships among subject areas to berecognized.
A Matrix Handbook for Statisticians addresses the need formatrix theory topics to be presented together in one book andfeatures a collection of topics not found elsewhere under onecover. These topics include:
* Complex matrices
* A wide range of special matrices and their properties
* Special products and operators, such as the Kroneckerproduct
* Partitioned and patterned matrices
* Matrix analysis and approximation
* Matrix optimization
* Majorization
* Random vectors and matrices
* Inequalities, such as probabilistic inequalities
Additional topics, such as rank, eigenvalues, determinants, norms, generalized inverses, linear and quadratic equations, differentiation, and Jacobians, are also included. The book assumesa fundamental knowledge of vectors and matrices, maintains areasonable level of abstraction when appropriate, and provides acomprehensive compendium of linear algebra results with use orpotential use in statistics. A Matrix Handbook for Statisticians isan essential, one-of-a-kind book for graduate-level courses inadvanced statistical studies including linear and nonlinear models, multivariate analysis, and statistical computing. It also serves asan excellent self-study guide for statistical researchers.
