Tutorial: Graphical Models and Bayesian Networks with R


Tutorial given at the useR! 2014 conference in Los Angeles
Søren Højsgaard, Department of Mathematical Sciences, Aalborg University, Denmark.

Goals

Introduce participants to using R for working with graphical models (in particular graphical log-linear models for discrete data (contingency tables)) and to probability propagation in Bayesian networks.

Outline

There will be a running example about building a probabilistic expert system for a medical diagnosis from real-world data.

Prerequisites

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

Further Information