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 John C. Nash - Marcel Dekker Inc
This book and software collection is intended to help scientists, engineers and statisticians in their work. We have collected various software tools for nonlinear parameter estimation, along with representative example problems.
by F. Baccelli, G. Cohen, G. J. Olsder, J. Quadrat - John Wiley & Sons
Presents new modelling and analysis techniques for the description of discrete event dynamic systems. Created within the text is a calculus which allows the derivation of analytical tools for computing the time behavior of this type of system.
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 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.