Asymptotic theory for large random matrices and its applications
Abstract/Contents
- Abstract
- Random matrix theory has a long history. It was first introduced in mathematical statistics by John Wishart in 1928, and it gained attention during the 1950s due to work by Eugene Wigner studying the distribution of nuclear energy levels. A large number of physicists and mathematicians have been fascinated by random matrix theory, and after decades of study, it has matured into a field with applications in many branches of physics and mathematics. Nowadays, the subject is still very much alive with new and exciting research. Much of my PhD work has revolved around the study of random matrix theory. This dissertation gives a tour of my work on asymptotic theory of large random matrices and its applications in statistics, probability, and the theory of orthogonal polynomials, respectively
Description
Type of resource | text |
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Form | electronic resource; remote; computer; online resource |
Extent | 1 online resource |
Place | California |
Place | [Stanford, California] |
Publisher | [Stanford University] |
Copyright date | 2020; ©2020 |
Publication date | 2020; 2020 |
Issuance | monographic |
Language | English |
Creators/Contributors
Author | Yan, Jun, (Researcher in random matrix theory) |
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Degree supervisor | Dembo, Amir |
Thesis advisor | Dembo, Amir |
Thesis advisor | Chatterjee, Sourav |
Thesis advisor | Montanari, Andrea |
Degree committee member | Chatterjee, Sourav |
Degree committee member | Montanari, Andrea |
Associated with | Stanford University, Computer Science Department. |
Subjects
Genre | Theses |
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Genre | Text |
Bibliographic information
Statement of responsibility | Jun Yan |
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Note | Submitted to Computer Science Department |
Thesis | Thesis Ph.D. Stanford University 2020 |
Location | electronic resource |
Access conditions
- Copyright
- © 2020 by Jun Yan
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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