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New Bayesian Lasso in Tobit Quantile Regression

Author

Listed:
  • Fadel Hamid Hadi ALHUSSEINI

    (University of Craiova, Romania)

Abstract

In this paper, we proposed a new hierarchy in Bayesian lasso through using scale mixture uniform (SMU) prior parameters in Tobit quantile regression (Tobit Q Reg) to achieve coefficients estimation and variables selection. SMU is considered a good replacement for scale mixture normal (SMN) to satisfy variable selection in Bayesian lasso (Tobit Q Reg). The Gibbs samplings are derived for all posterior distributions. The performance assessment of the method proposed versus other methods is done through simulation examples and real data.

Suggested Citation

  • Fadel Hamid Hadi ALHUSSEINI, 2017. "New Bayesian Lasso in Tobit Quantile Regression," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(6), pages 213-229, June.
    • Handle: RePEc:rsr:supplm:v:65:y:2017:i:6:p:213-229
    as

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    References listed on IDEAS

    as
    1. Fair, Ray C, 1978. "A Theory of Extramarital Affairs," Journal of Political Economy, University of Chicago Press, vol. 86(1), pages 45-61, February.
    2. Bilias, Yannis & Chen, Songnian & Ying, Zhiliang, 2000. "Simple resampling methods for censored regression quantiles," Journal of Econometrics, Elsevier, vol. 99(2), pages 373-386, December.
    3. Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
    4. Ji, Yonggang & Lin, Nan & Zhang, Baoxue, 2012. "Model selection in binary and tobit quantile regression using the Gibbs sampler," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 827-839.
    5. Chernozhukov, Victor & Hansen, Christian, 2008. "Instrumental variable quantile regression: A robust inference approach," Journal of Econometrics, Elsevier, vol. 142(1), pages 379-398, January.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    New Bayesian lasso; MCMC; Tobit Quantile Regression; scale mixture uniform ; variable selection;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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