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portada Spectral Analysis of Large Dimensional Random Matrices (Springer Series in Statistics) (in English)
Type
Physical Book
Publisher
Year
2010
Language
English
Pages
568
Format
Hardcover
Weight
2.06
ISBN
9781441906601
ISBN13
9781441906601

Spectral Analysis of Large Dimensional Random Matrices (Springer Series in Statistics) (in English)

Zhidong Bai; Jack W. Silverstein (Author) · Springer · Hardcover

Spectral Analysis of Large Dimensional Random Matrices (Springer Series in Statistics) (in English) - Zhidong Bai; Jack W. Silverstein

Physical Book

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Synopsis "Spectral Analysis of Large Dimensional Random Matrices (Springer Series in Statistics) (in English)"

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 knowledge of matrix theory and an understanding of probability theory at the graduate level, who desire to learn the concepts and tools in solving problems in this area. It can also serve as a detailed handbook on results of large dimensional random matrices for practical users. This second edition includes two additional chapters, one on the authors' results on the limiting behavior of eigenvectors of sample covariance matrices, another on applications to wireless communications and finance. While attempting to bring this edition up-to-date on recent work, it also provides summaries of other areas which are typically considered part of the general field of random matrix theory.

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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Hardcover.

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