Random Matrix Models and Their Applications
by Pavel Bleher, Alexander Its
Publisher: Cambridge University Press 2001
Number of pages: 438
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. Its focus on the interaction between physics and mathematics will make it a welcome addition to the shelves of graduate students and researchers in both fields, as will its expository emphasis.
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by David Aldous, James Allen Fill - University of California, Berkeley
From the table of contents: General Markov Chains; Reversible Markov Chains; Hitting and Convergence Time, and Flow Rate, Parameters for Reversible Markov Chains; Special Graphs and Trees; Cover Times; Symmetric Graphs and Chains; etc.
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 G. D'Agostini - arXiv
Triggered by a recent interesting article on the too frequent incorrect use of probabilistic evidence in courts, the author introduces the basic concepts of probabilistic inference with a toy model, and discusses several important issues.
by Hossein Pishro-Nik - Kappa Research, LLC
This book introduces students to probability, statistics, and stochastic processes. It can be used by both students and practitioners in engineering, sciences, finance, and other fields. It provides a clear and intuitive approach to these topics.