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Mat-1.3608 Markov chains, spring 2008 (3-5 (new) credits)

The purpose of the course is to give mathematical background for Markov Chain Monte Carlo (MCMC) simulation methodology.

Course and exercises give 3 credits. Additional credits possible with project work.

The course is lectured during the third period of the academic year 2007-2008.

Feedback: please, fill in the feedback form available at Opinions-Online.

Prerequisites (recommended):
Mat-1.2600 Applied probability A
Mat-2.3111 Stochastic processes

Contents (preliminary):
1. Markov chains
2. Irreducibility, aperiodicity, reversebility and stationarity
3. Law of large numbers
4. Central limit theorem
5. MCMC
6. MCMC algorithms

Lectures: Tue 10-12 U356, Fri 10-12 U356, beginning Fri 18.1.2008.

Professor Esko Valkeila

Exams:
15.3.2008 10-13

Exercises: Thu 14-16 U356.

Assistant Heikki Tikanmäki

Exercise 1
Exercise 2
Exercise 3
Exercise 4
Exercise 5
Exercise 6

Course material:

• Olle Häggström: Finite Markov Chains and Algorithmic Applications. London Mathematical Society, Student Texts 52, Cambridge University Press, 2002
• Esa Nummelin: MC's for MCMC'ists. International Statistical Review, 70, 215-240, 2002.