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Power Prior Elicitation in Bayesian Quantile Regression

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  • Rahim Alhamzawi
  • Keming Yu

Abstract

We address a quantile dependent prior for Bayesian quantile regression. We extend the idea of the power prior distribution in Bayesian quantile regression by employing the likelihood function that is based on a location-scale mixture representation of the asymmetric Laplace distribution. The propriety of the power prior is one of the critical issues in Bayesian analysis. Thus, we discuss the propriety of the power prior in Bayesian quantile regression. The methods are illustrated with both simulation and real data.

Suggested Citation

  • Rahim Alhamzawi & Keming Yu, 2011. "Power Prior Elicitation in Bayesian Quantile Regression," Journal of Probability and Statistics, Hindawi, vol. 2011, pages 1-16, December.
    • Handle: RePEc:hin:jnljps:874907
    DOI: 10.1155/2011/874907
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    Cited by:

    1. R. Alhamzawi & K. Yu & D. F. Benoit, 2011. "Bayesian adaptive Lasso quantile regression," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/728, Ghent University, Faculty of Economics and Business Administration.
    2. Mani Suleiman & Haydar Demirhan & Leanne Boyd & Federico Girosi & Vural Aksakalli, 2022. "Bayesian prediction of emergency department wait time," Health Care Management Science, Springer, vol. 25(2), pages 275-290, June.

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