Bayesian adaptive Lasso Tobit regression
Journal of Al-Qadisiyah for Computer Science and Mathematics
2019, Volume 11, Issue 1, Pages Stat Page 1-10
2019, Volume 11, Issue 1, Pages Stat Page 1-10
Abstract
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.
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