USE BAYESIAN ADAPTIVE LASSO FOR TOBIT REGRESSION WITH REAL DATA

ABSTRACT

Restricted data plays a significant role in describing economic, social, medical, with other phenomena. Most of the time the Restricted point on zero, so the appropriate regression model for this type of data is a Tobit regression model. When the number of independent variables is too large, the process of their interpretation is very complex. To get around this problem, it is possible to use Variable Selections. In the current paper, we will use the adaptive Lasso through the Bayesian method. Also, the Bayesians Lasso method has many advantages that provide accuracy in the results, especially in the selection of Variable Selections. To compare our proposal, we will use the number of infections with Covid-19 for a group of families through a field survey in Al-Qadisiyah Governorate and identify the effective factors. © 2021 DAV College. All rights reserved.