During the last decades, Bayesian statistics has gained enormous
popularity as an elegant and powerful computational tool to perform
statistical analysis in complex stochastic models as applied in
engineering, science and medicine. Bayesian statistics offers an
alternative approach to traditional data analysis by including prior
knowledge about the model parameters in form of a prior
distribution. Using Bayes formula, the prior distribution is updated
to the posterior distribution by incorporating the observed data by
means of the likelihood. Subsequently statistical inference about the
unknown model parameters is derived from the posterior
distribution. However, the posterior distribution is often intractable
due to high-dimensional complex integrals, implying that approximate
stochastic simulation techniques such as Markov Chain Monte Carlo
(MCMC) methods become crucial.
This course reviews the basics ideas behind Bayesian statistics and
MCMC methods. Background on Markov chains will be provided and
subjects such as Metropolis and Metropolis-Hastings algorithms, Gibbs
sampling, and output analysis will be discussed. Furthermore,
graphical models will be introduced as a convenient tool to model
complex dependency structures within a stochastic model. The theory
will be demonstrated through different examples of applications and
exercises, partly based on the software packages R, BUGS and JAGS.
Prerequisites: The course is accessible to those new to these
subjects; however, a basic knowledge of statistics and probability
theory, as obtained through engineering studies at Aalborg University,
Kasper K. Berthelsen, Associate Professor, email: email@example.com
Associate Professor Kasper K. Berthelsen and Head of Department Søren Højsgaard, email: firstname.lastname@example.org
May 16-17 (room G5-109), May 23-24 (room G5-112) and June 3-4 (Niels Jernes Vej 14, Room 4-107), 2013. Each day from 9am to 4pm.
Niels Jernes Vej 14
Number of seats:
April 22, 2013
Important information concerning PhD courses
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.