Bayesian adaptive Lasso Tobit regression

الملخص EN

In this paper, we introduce a new procedure for model selection in Tobit regression, we suggest the Bayesian adaptive Lasso Tobit regression (BALTR) for variable selection (VS) and coefficient estimation.

We submitted a Bayesian hierarchical model and Gibbs sampler (GS) for our procedure.

Our proposed procedure is clarified by means of simulations and a real data analysis.

Results demonstrate our procedure performs well in comparison to further procedures