| 書目名稱 | Spectral Analysis of Large Dimensional Random Matrices | | 編輯 | Zhidong Bai,Jack W. Silverstein | | 視頻video | http://file.papertrans.cn/874/873810/873810.mp4 | | 概述 | Includes supplementary material: | | 叢書名稱 | Springer Series in Statistics | | 圖書封面 |  | | 描述 | .The aim of the book is to introduce basic concepts, main results, and widely applied mathematical tools in the spectral analysis of large dimensional random matrices. The core of the book focuses on results established under moment conditions on random variables using probabilistic methods, and is thus easily applicable to statistics and other areas of science. The book introduces fundamental results, most of them investigated by the authors, such as the semicircular law of Wigner matrices, the Marcenko-Pastur law, the limiting spectral distribution of the multivariate .F. matrix, limits of extreme eigenvalues, spectrum separation theorems, convergence rates of empirical distributions, central limit theorems of linear spectral statistics, and the partial solution of the famous circular law. While deriving the main results, the book simultaneously emphasizes the ideas and methodologies of the fundamental mathematical tools, among them being: truncation techniques, matrix identities, moment convergence theorems, and the Stieltjes transform. Its treatment is especially fitting to the needs of mathematics and statistics graduate students and beginning researchers, having a basic knowl | | 出版日期 | Book 2010Latest edition | | 關(guān)鍵詞 | Eigenvalue; Eigenvector; Fitting; Matrix; Matrix Theory; Random variable | | 版次 | 2 | | doi | https://doi.org/10.1007/978-1-4419-0661-8 | | isbn_softcover | 978-1-4614-2592-2 | | isbn_ebook | 978-1-4419-0661-8Series ISSN 0172-7397 Series E-ISSN 2197-568X | | issn_series | 0172-7397 | | copyright | Springer-Verlag New York 2010 |
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