A New Bayesian Group Bridge to Solve the Tobit Model

Saja  Aljanabi; Rahim  Alhamzawi

doi:10.24996/ijs.2020.SI.1.29

Authors

Saja Aljanabi Statistics Department, College of Administration and Economics, University of Al-Qadisiyah, Al Diwaniyah, Iraq
Rahim Alhamzawi Statistics Department, College of Administration and Economics, University of Al-Qadisiyah, Al Diwaniyah, Iraq

DOI:

https://doi.org/10.24996/ijs.2020.SI.1.29

Keywords:

left- censored regression, variable selection, Bayesian group Bridge left- censored regression (BGBRLC)

Abstract

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.