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MAI0028
Markov chain Monte Carlo and baysian statistics

Number of credits: 12 hp

Examiner: Timo Koski

Course literature: C.P Roberts (2201): The Bayesian Choise. Second Edition, Springer Verlage. Olle Häggströrm (2002): Finite Markov chains and alogrithmnic applications. London Mathematical Society Student Text 52. Cambridge. Timo Koski (2005): Förläsningsanteckningar tillgängliga.

Course contents: From Prior Information to Prior Distribution, Bayesian Point Estimation, Tests and Confidence Region, Essentials of Markov chains for MCMC, Bayesian Computation, MCMC for Estimating Posterior Quantities, Reversible Jump Markov chains, Sumulated Annealing, BUGS

Organisation:

Examination: Home exercises.

Prerequisites:

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Last updated: 2014-04-29