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Bayesian adaptive Lasso Tobit regression | ||
| Journal of Al-Qadisiyah for Computer Science and Mathematics | ||
| Article 1, Volume 11, Issue 1, 2019, Pages 1-10 PDF (0 K) | ||
| Authors | ||
| Haider Kadhim Abbas; Rahim Jabbar Thaher | ||
| 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. | ||
| Keywords | ||
| Tobit regression; Bayesian adaptive Lasso Tobit regression; Variable selection | ||
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