We relate two approaches; Bayesian partitioning and log-linear modelling.
We derive theoretical results on this relation, plus results based on simulations.
Illustrations show that partitioning can assist log-linear model search.
Detecting marginally independent covariates assists the search for interactions.
The main advantage concerns sparse contingency tables.