Advanced Stochastic Processes
by Jan A. Van Casteren
Publisher: Bookboon 2013
Number of pages: 404
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, the martingale problem, Ito calculus, cylindrical measures, ergodic theory, etc.
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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.
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 Matt Scott - University of Waterloo
This book is designed as an introduction to the ideas and methods used to formulate mathematical models of physical processes in terms of random functions. A senior undergraduate course offered to students with a suitably mathematical background.
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.