Introduction to Stochastic Analysis
by Michael Roeckner
Publisher: Universitaet Bielefeld 2011
Number of pages: 98
From the table of contents: Introduction to Pathwise Ito-Calculus; (Semi-)Martingales and Stochastic Integration; Markov Processes and Semigroups - Application to Brownian Motion; Girsanov Transformation; Time Transformation.
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by Marek Biskup - arXiv
Recent progress on understanding of the Random Conductance Model is reviewed and commented. A particular emphasis is on the results on the scaling limit of the random walk among random conductances for almost every realization of the environment.
by John Venn - Macmillan And Company
No mathematical background is necessary for this classic of probability theory. It remains unsurpassed in its clarity, readability, and charm. It commences with physical foundations, examines logical superstructure, and explores various applications.
by Remco van der Hofstad - Eindhoven University of Technology
These lecture notes are intended to be used for master courses, where the students have a limited prior knowledge of special topics in probability. We have included many of the preliminaries, such as convergence of random variables, etc.
by Davar Khoshnevisan, Firas Rassoul-Agha - University of Utah
This is a first course in undergraduate probability. It covers standard material such as combinatorial problems, random variables, distributions, independence, conditional probability, expected value and moments, law of large numbers, etc.