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Uedu Open / Advanced Stochastic Processes
15.070J

Advanced Stochastic Processes

Prof. David Gamarnik | Fall 2013
Science & Math Mathematics Probability and Statistics
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CC BY-NC-SA 4.0
Course introduction
This class covers the analysis and modeling of stochastic processes. 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.
Course Information
SourceMIT 開放式課程
DepartmentElectrical Engineering and Computer Science
LanguageEnglish
Number of videos0
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