Probability Theory and Stochastic Processes with Applications
by Oliver Knill
Publisher: Overseas Press 2009
Number of pages: 382
This text covers material of a basic probability course, discrete stochastic processes including Martingale theory, continuous time stochastic processes like Brownian motion and stochastic differential equations, estimation theory, Vlasov dynamics, multi-dimensional moment problems, random maps, etc.
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by Gordan Žitković - The University of Texas at Austin
Contents: Probability review; Mathematica in 15 minutes; Stochastic Processes; Simple random walk; Generating functions; Random walks - advanced methods; Branching processes; Markov Chains; The 'Stochastics' package; Classification of States; etc.
by Daniel W. Stroock - Tata Institute of Fundamental Research
The author's purpose in these lectures was to provide some insight into the properties of solutions to stochastic differential equations. In order to read these notes, one need only know the basic Ito theory of stochastic integrals.
by Anders Szepessy, et al. - KTH
The goal of this course is to give useful understanding for solving problems formulated by stochastic differential equations models in science, engineering and finance. Typically, these problems require numerical methods to obtain a solution.
by K. Ito - Tata Institute of Fundamental Research
The book discusses the elementary parts of Stochastic Processes from the view point of Markov Processes. Topics: Markov Processes; Srong Markov Processes; Multi-dimensional Brownian Motion; Additive Processes; Stochastic Differential Equations; etc.