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Matrix Algebra Paperback English by James E. Gentle - 01 Nov 2017

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PublisherSpringer International Publishing AG
ISBN 139783319648668
ISBN 103319648667
Book SubtitleTheory Computations And Applications In Statictics
Book DescriptionMatrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. This much-needed work presents the relevant aspects of the theory of matrix algebra for applications in statistics. It moves on to consider the various types of matrices encountered in statistics, such as projection matrices and positive definite matrices, and describes the special properties of those matrices. Finally, it covers numerical linear algebra, beginning with a discussion of the basics of numerical computations, and following up with accurate and efficient algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors.
Editorial ReviewGentle has put in a lot of time and effort to writing this book with careful attention to details. ... it is all needed to make sure the student has a firm and solid understanding of matrix algebra on the graduate level. I would recommend this book for all those who teach graduate level matrix algebra or ... to those undergraduate students who wish to have an independent study.
About the AuthorJames E. Gentle, PhD, is University Professor of Computational Statistics at George Mason University. He is a Fellow of the American Statistical Association (ASA) and of the American Association for the Advancement of Science. Professor Gentle has held several national offices in the ASA and has served as editor and associate editor of journals of the ASA as well as for other journals in statistics and computing. He is author of Random Number Generation and Monte Carlo Methods (Springer, 2003) and Computational Statistics (Springer, 2009)
LanguageEnglish
AuthorJames E. Gentle
Edition Number2
Publication Date01 Nov 2017
Number of Pages648

Matrix Algebra Paperback English by James E. Gentle - 01 Nov 2017

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