Topics in Random Matrix Theory
by Terence Tao
Number of pages: 340
This is a textbook for a graduate course on random matrix theory, inspired by recent developments in the subject. This text focuses on foundational topics in random matrix theory upon which the most recent work has been based.
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by G. Jay Kerns
A textbook for an undergraduate course in probability and statistics. The prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
by Matthias Vallentin
The cookbook contains a succinct representation of various topics in probability theory and statistics. It provides a comprehensive reference reduced to the mathematical essence, rather than aiming for elaborate explanations.
by Pavel Bleher, Alexander Its - Cambridge University Press
The book covers broad areas such as topologic and combinatorial aspects of random matrix theory; scaling limits, universalities and phase transitions in matrix models; universalities for random polynomials; and applications to integrable systems.
by O. Melchert - arXiv
In these lecture notes, a selection of frequently required statistical tools will be introduced and illustrated. They allow to post-process data that stem from, e.g., large-scale numerical simulations (aka sequence of random experiments).