Almost None of the Theory of Stochastic Processes
by Cosma Rohilla Shalizi
Publisher: Carnegie Mellon University 2010
Number of pages: 347
This is intended to be a second course in stochastic processes. It is assumed that you have had a first course on stochastic processes, using elementary probability theory. You will be re-studying stochastic processes within the framework of measure-theoretic probability.
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by David Nualart - The University of Kansas
From the table of contents: Stochastic Processes (Probability Spaces and Random Variables, Definitions and Examples); Jump Processes (The Poisson Process, Superposition of Poisson Processes); Markov Chains; Martingales; Stochastic Calculus.
by Pierre Simon Laplace - Chapman & Hall
Classic book on probability theory. It demonstrates, without the use of higher mathematics, the application of probability to games of chance, physics, reliability of witnesses, astronomy, insurance, democratic government, and many other areas.
by Gian-Carlo Rota - David Ellerman
In 1999, Gian-Carlo Rota gave his famous course, Probability, at MIT for the last time. The late John N. Guidi taped the lectures and took notes which he then wrote up in a verbatim manner conveying the substance and the atmosphere of the course.
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.