Id: 041732 Credits Min: 3 Credits Max: 3

Description

An introduction to the theory, algorithms, approximations, and applications of stochastic processes. Topics studied include Markov chain and continuous and continuous time Markov process models and applications, renewal processes, Brownian Motion, analytical and numerical approximation methods, Markov decision processes. Application areas include inventory control, reliability, queuing, and decision analysis.

Prerequisites

MATH.3860 Probability and Statistics.

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