• Title: Advanced Stochastic Processes
• Author(s) David Gamarnik
• Publisher: Massachusetts Institute of Technology
• Hardcover/Paperback: N/A
• eBook: PDF Files
• Language: English
• ISBN-10/ASIN: N/A
• ISBN-13: N/A
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Book Description

This guide to Stochastic Processes covers a wide range of topics. Short, readable chapters aim for clarity rather than full generality. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide exercises in the application of simple stochastic analysis to realistic problems.

Topics include measure theoretic probability, martingales, filtration, and stopping theorems, elements of large deviations theory, Brownian motion and reflected Brownian motion, stochastic integration and Ito calculus and functional limit theorems. In addition, the class will go over some applications to finance theory, insurance, queueing and inventory models.

• David Gamarnik is a Professor of Operations Research at MIT Sloan School of Management.

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• Probability, Stochastic Process, Queueing Theory, etc.
• Statistics, and SAS Programming
• Geometry and Topology
• Combinatorics and Game Theory

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