Concentration of the spectral measure of large Wishart matrices with dependent entries
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1. | Title | Title of document | Concentration of the spectral measure of large Wishart matrices with dependent entries |
2. | Creator | Author's name, affiliation, country | Adityanand Guntuboyina; Yale University |
2. | Creator | Author's name, affiliation, country | Hannes Leeb; Yale University |
3. | Subject | Discipline(s) | |
3. | Subject | Keyword(s) | Wishart matrices, concentration inequalities, spectral measure |
3. | Subject | Subject classification | Primary 15A52 Secondary 60F10, 15A18 |
4. | Description | Abstract | We derive concentration inequalities for the spectral measure of large random matrices, allowing for certain forms of dependence. Our main focus is on empirical covariance (Wishart) matrices, but general symmetric random matrices are also considered. |
5. | Publisher | Organizing agency, location | |
6. | Contributor | Sponsor(s) | |
7. | Date | (YYYY-MM-DD) | 2009-08-12 |
8. | Type | Status & genre | Peer-reviewed Article |
8. | Type | Type | |
9. | Format | File format | |
10. | Identifier | Uniform Resource Identifier | http://ecp.ejpecp.org/article/view/1483 |
10. | Identifier | Digital Object Identifier | 10.1214/ECP.v14-1483 |
11. | Source | Journal/conference title; vol., no. (year) | Electronic Communications in Probability; Vol 14 |
12. | Language | English=en | |
14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
15. | Rights | Copyright and permissions | The Electronic Journal of Probability applies the Creative Commons Attribution License (CCAL) to all articles we publish in this journal. Under the CCAL, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles published in EJP, so long as the original authors and source are credited. This broad license was developed to facilitate open access to, and free use of, original works of all types. Applying this standard license to your work will ensure your right to make your work freely and openly available. Summary of the Creative Commons Attribution License You are free
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