Model Uncertainty and Missing Data: An Objective Bayesian Perspective
Model Uncertainty and Missing Data: An Objective Bayesian Perspective
The interplay between missing data and model uncertainty -- two classic statistical problems -- leads to primary questions that we formally address from an objective Bayesian perspective. For the general regression problem, we discuss the probabilistic justification of Rubin's rules applied to the usual components of Bayesian variable selection, arguing …