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.
Download or read it online for free here:
by S.P. Meyn, R.L. Tweedie - Springer
The book on the theory of general state space Markov chains, and its application to time series analysis, operations research and systems and control theory. An advanced graduate text and a monograph treating the stability of Markov chains.
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 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 H. Kunita - Tata Institute Of Fundamental Research
The author presents basic properties of stochastic flows, specially of Brownian flows and their relations with local characteristics and with stochastic differential equations. Various limit theorems for stochastic flows are presented.