A New Bayesian Group Bridge to Solve the Tobit Model
left- censored regression
variable selection
Bayesian group Bridge left- censored regression (BGBRLC)
In this paper, we propose a new approach of regularization for the left censored data (Tobit). Specifically, we propose a new Bayesian group Bridge for left-censored regression ( BGBRLC). We developed a new Bayesian hierarchical model and we suggest a new Gibbs sampler for posterior sampling. The results show that the new approach performs very well compared to some existing approaches.
