Pitt | Swanson Engineering
Courses
Industrial Engineering Course Description

IE 3099 - THEORY OF STOCHASTIC STIMULATION


This course focuses on the theoretical foundations of simulation methodology and its recent advances with an emphasis on stochastic processes. Topics include: generating random objects, output analysis (autoregressive, regenerative, spectral, and stationary times series methods), variance reduction techniques (antithetic variable, common random numbers, control variables), Markov chain Monte Carlo (MCMC), rare-event simulation techniques, stochastic optimization (likelihood ratio method, perturbation analysis, stochastic approximation), sampling of stochastic differential equation, exact simulation and prefect sampling. Some of the motivating applications that will be discussed are drawn from the domain of finance and risk management, insurance modeling, and queuing networks.

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