Variable Selection for Censored Regression Models

In many situations, we are interested in selection of important variables which are adequate for prediction under a censored regression model (known as the " Tobit " model). In this paper, some selection procedures based on the information theoretic criteria are proposed, and these procedures are proved to be consistent.