Introduction to Stochastic Processes
by Gordan Žitković
Publisher: The University of Texas at Austin 2010
Number of pages: 107
Contents: Probability review; Mathematica in 15 minutes; Stochastic Processes; The simple random walk; Generating functions; Random walks - advanced methods; Branching processes; Markov Chains; The 'Stochastics' package; Classification of States; More on Transience and recurrence; Absorption and reward; Stationary and Limiting Distribution; Solved Problems.
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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 M. Gubinelli, N. Perkowski - arXiv
The aim is to introduce the basic problems of non-linear PDEs with stochastic and irregular terms. We explain how it is possible to handle them using two main techniques: the notion of energy solutions and that of paracontrolled distributions.
by Jan A. Van Casteren - Bookboon
In this book, which is basically self-contained, the following topics are treated thoroughly: Brownian motion as a Gaussian process, Brownian motion as a Markov process, Brownian motion as a martingale, Markov chains, renewal theory, etc.