Asymptotic theory for large random matrices and its applications

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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
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)
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
Genre Text

Bibliographic information

Statement of responsibility Jun Yan
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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