Short course: Graphical Models and Bayesian Networks with R

July 3rd, (prior to the 31th International Workshop on Statistical Modelling, Rennes, France

Presenter:

Søren Højsgaard, Department of Mathematical Sciences, Aalborg University, Denmark

Goals:

Introduce participants to working with Graphical Models (GMs) and Bayesian Networks (BNs) in R. This includes probability propagation in BNs and aspects of learning BNs from data using GMs.

Topics will include:

Examples from genetics will be used throughout for illustrative purposes. Moreover, there will be a running example about building a BN for a medical diagnosis from real-world data.

Prerequisites:

Attendees are assumed to have a working understanding of log-linear models for contingency tables.

Preparing for the course:

Bring a laptop with the most recent version of R installed. Moreover you should install the necessary packages as:

Course material

Slides/notes are available here

See also http://www.csse.monash.edu.au/bai/book/BAI_Chapter2.pdf

See also http://anthro.palomar.edu/mendel/mendel_1.htm

Literature:

Højsgaard, S.; Edwards, D.; Lauritzen, S. (2012): Graphical models with R, Springer. The book is available from amazon for about 40 GBP.