| 书目名称 | Numerical Linear Algebra for Applications in Statistics | | 编辑 | James E. Gentle | | 视频video | | | 丛书名称 | Statistics and Computing | | 图书封面 |  | | 描述 | Numerical linear algebra is one of the most important subjects in the field of statistical computing. Statistical methods in many areas of application require computations with vectors and matrices. This book describes accurate and efficient computer algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors. Although the book is not tied to any particular software system, it describes and gives examples of the use of modern computer software for numerical linear algebra. An understanding of numerical linear algebra requires basic knowledge both of linear algebra and of how numerical data are stored and manipulated in the computer. The book begins with a discussion of the basics of numerical computations, and then describes the relevant properties of matrix inverses, matrix factorizations, matrix and vector norms, and other topics in linear algebra; hence, the book is essentially self- contained. The topics addressed in this bookconstitute the most important material for an introductory course in statistical computing, and should be covered in every such course. The book includes exercises and can be used as a text for a firs | | 出版日期 | Textbook 1998 | | 关键词 | Analysis; Eigenvalue; Eigenvector; Fitting; Matrix; algebra; algorithms; best fit; computer; linear algebra; s | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4612-0623-1 | | isbn_softcover | 978-1-4612-6842-0 | | isbn_ebook | 978-1-4612-0623-1Series ISSN 1431-8784 Series E-ISSN 2197-1706 | | issn_series | 1431-8784 | | copyright | Springer Science+Business Media New York 1998 |
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发表于 2025-3-21 18:04:12
