Bayesian Methods HT23

The course covers Bayes' formula, informative and non-informative prior distributions, posterior distributions, single- and multiparameter distributions like binomial, multinomial och normal distributions, hierarchical models, linear models, Bayesian inference and goodness-of-fit measures and stochastic simulation with MCMC (Markov Chain Monte Carlo).

Course literature: "Bayesian Methods for Data Analysis" by B.P. Carlin and T.A. Louis,Chapman and Hall/CRC Press, 2009 (3rd ed).

Course responsible: Chun-Biu Li and Felix Günther

Please note that self-enrollment on the course page is not the same as course registration in Ladok.

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IMPORTANT:

The teaching of the whole course will be carried out ON CAMPUS

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