Table of Contents

A course on Markov Chains: Advanced topics

Registration to the course

Program of the course

Prof Chapters Topics Material
24/09 (AD) Chapt. 1 and 2. Conditional distribution, their construction and related operations. Introduction to Markov chains, first definitions Exercise sheet 1 Lecture notes Notes Monte Carlo
01/10 (AD) Chapt. 2 and 3 Invariant measures / reversibility, Canonical space. Exercise sheet 2 Exercise sheet 3 Reminders Conditonal expectation Exercises conditional expectation
08/10 (AD) Canceled course
15/10 (AD) Chapt. 3 Canonical space (continued). Kolmogorov extension theorem. Strong Markov property, Stopping times, return and hitting times, consequences of Markov property. Exercise sheet 4 and Exercise sheet 5 and Written notes Password: AODMDA4@1;R4e
22/10 No course
05/11 (AD) Chap 5 Dynamical systems, Birkhoff theorem, Law of Large Number for Markov chains
12/11 (RD) Chapt. 18 Uniform and Geometric ergodicity
19/11 (RD) Chapt. 21 Central limit theorems
26/11 (RD) Chap 22 Spectral theory
3/12 (RD)
10/12 (RD)

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Contact

name email adresses
Alain Durmus alain.durmus “Arobase” polytechnique.edu
Randal Douc randal.douc “Arobase” polytechnique.edu