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 S.P. Meyn, R.L. Tweedie - Springer
The book on the theory of general state space Markov chains, and its application to time series analysis, operations research and systems and control theory. An advanced graduate text and a monograph treating the stability of Markov chains.
by Thomas G. Kurtz - University of Wisconsin
Covered topics: stochastic integrals with respect to general semimartingales, stochastic differential equations based on these integrals, integration with respect to Poisson measures, stochastic differential equations for general Markov processes.
by Oscar Sheynin - arXiv.org
This book covers the history of probability up to Kolmogorov with essential additional coverage of statistics up to Fisher. The book covers an extremely wide field, and is targeted at the same readers as any other book on history of science.
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This book is an introduction to probability and mathematical statistics intended for students already having some elementary mathematical background. It is intended for a one-year junior or senior level undergraduate or beginning graduate course.