Given a decomposable graph, we characterize and enumerate the set of pairs of vertices whose connection or disconnection results in a new graph that is also decomposable. We discuss the relevance of this results to Markov chain Monte Carlo methods that sample or optimize over the space of decomposable graphical models according to probabilities determined by a posterior distribution given observed multivariate data.
|Number of pages||7|
|Journal||Computational Statistics & Data Analysis|
|Publication status||Published - 2009|
- Graphical models, model estimation, triangulated graphs, chordal graphs, Markov chain Monte Carlo methods.