Spectral analysis of large dimensional random matrices
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 t...
Enregistré dans:
| Auteurs principaux: | , |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Édition: | 2nd ed. 2010. |
| Collection: | Springer Series in Statistics
|
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Spectral analysis of large dimensional random matrices, Zhidong Bai, Jack W. Silverstein, 2nd edition, New York, Springer, 2010, 1 vol. (XVI- 551 p.), Springer series in statistics, 978-1-441-90660-1 • Spectral Analysis of Large Dimensional Random Matrices, Texte imprimé, 9781441906625 • Spectral Analysis of Large Dimensional Random Matrices, Texte imprimé, 9781461425922 |
Table des matières:
- Wigner Matrices and Semicircular Law Sample Covariance Matrices and the Mar#x010D;enko-Pastur Law Product of Two Random Matrices Limits of Extreme Eigenvalues Spectrum Separation Semicircular Law for Hadamard Products Convergence Rates of ESD CLT for Linear Spectral Statistics Eigenvectors of Sample Covariance Matrices Circular Law Some Applications of RMT