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MATH 396 A: Finite Markov Chains and Monte-Carlo Methods

Meeting Time: 
MWF 10:30am - 11:20am
Location: 
CDH 139
SLN: 
16615
Joint Sections: 
STAT 396 A
Instructor:
Photo of Soumik Pal
Soumik Pal
Catalog Description: 
Finite Markov chains; stationary distributions; time reversals; classification of states; classical Markov chains; convergence in total variation distance and L2; spectral analysis; relaxation time; Monte Carlo techniques: rejection sampling, Metropolis-Hastings, Gibbs sampler, Glauber dynamics, hill climb and simulated annealing; harmonic functions and martingales for Markov chains. Prerequisite: a minimum grade of 2.0 in MATH 308; and either a minimum grade of 2.0 in MATH 394/STAT 394 and STAT 395/MATH 395, or a minimum grade of 2.0 in STAT 340 and STAT 341, or a minimum grade of 2.0 in STAT 340 and STAT 395/MATH 395. Offered: jointly with STAT 396; Sp.
GE Requirements: 
Natural World (NW)
Credits: 
3.0
Status: 
Active
Last updated: 
March 23, 2020 - 2:30am
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