| 书目名称 | Matrix Algebra | | 副标题 | Theory, Computations | | 编辑 | James E. Gentle | | 视频video | | | 概述 | This book‘s emphasis is on the areas of matrix analysis that are important for statisticians.Addresses computational issues, places more emphasis on applications that existing texts and is written in | | 丛书名称 | Springer Texts in Statistics | | 图书封面 |  | | 描述 | .Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. The first part of this book presents the relevant aspects of the theory of matrix algebra for applications in statistics. This part begins with the fundamental concepts of vectors and vector spaces, next covers the basic algebraic properties of matrices, then describes the analytic properties of vectors and matrices in the multivariate calculus, and finally discusses operations on matrices in solutions of linear systems and in eigenanalysis. This part is essentially self-contained...The second part of the book begins with a consideration of various types of matrices encountered in statistics, such as projection matrices and positive definite matrices, and describes the special properties of those matrices. The second part also describes some of the many applications of matrix theory in statistics, including linear models, multivariate analysis, and stochastic processes. The brief coverage in this part illustrates the matrix theory developed in the first part of the book. The first two parts of the book can be used as the text for a course in matrix algebra for statistics | | 出版日期 | Textbook 20071st edition | | 关键词 | Algebra; STATISTICA; algorithm; algorithms; calculus; data analysis; eigenanalysis; matrix factorization; ma | | 版次 | 1 | | doi | https://doi.org/10.1007/978-0-387-70873-7 | | isbn_ebook | 978-0-387-70873-7Series ISSN 1431-875X Series E-ISSN 2197-4136 | | issn_series | 1431-875X | | copyright | Springer-Verlag New York 2007 |
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发表于 2025-3-21 18:28:19
