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 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 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 F.P. Kelly - John Wiley and Sons Ltd
The book on vector stochastic processes in equilibrium or stochastic networks, with wide range of applications. It covers the concept of reversibility, the output from a queue, and the epolymerization process quilibrium distribution.
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.