Bayesian Variable Selection in Qualitative Models by Kullback-Leibler Projections.

The Bayesian variable selection method proposed in the paper is based on the evaluation of the Kullback-Leibler distance between the full (or encompassing) model and the submodels. The emplmentation of the model doesnot require a separate prior modeling on the submodels since the corresponding parameters for the submodels are defined as the kullback-Leibler projections of the full model parameters. The result of the selection procedure is the submodel with the smallest number of covariates which is at an acceptable distance of the full model.