ACM 216 - Markov Chains, Discrete Stochastic Processes and Applications

Institution:

California Institute of Technology

Subject:

Applied and Computational Mathematics

Description:

Stable laws, Markov chains, classification of states, ergodicity, von Neumann ergodic theorem, mixing rate, stationary/equilibrium distributions and convergence of Markov chains, Markov chain Monte Carlo and its applications to scientific computing, Metropolis Hastings algorithm, coupling from the past, martingale theory and discrete time martingales, rare events, law of large deviations, Chernoff bounds. Instructor: Owhadi.

Credits:

9.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.caltech.edu

Phone Number:

(626) 395-6811

Regional Accreditation:

Western Association of Schools and Colleges

Calendar System:

Quarter

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