IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v107y2015icp18-26.html
   My bibliography  Save this article

A sandwich likelihood correction for Bayesian quantile regression based on the misspecified asymmetric Laplace density

Author

Listed:
  • Sriram, Karthik

Abstract

A sandwich likelihood correction is proposed to remedy an inferential limitation of the Bayesian quantile regression approach based on the misspecified asymmetric Laplace density, by leveraging the benefits of the approach. Supporting theoretical results and simulations are presented.

Suggested Citation

  • Sriram, Karthik, 2015. "A sandwich likelihood correction for Bayesian quantile regression based on the misspecified asymmetric Laplace density," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 18-26.
    • Handle: RePEc:eee:stapro:v:107:y:2015:i:c:p:18-26
    DOI: 10.1016/j.spl.2015.07.035
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S016771521500276X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2015.07.035?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yu, Keming & Moyeed, Rana A., 2001. "Bayesian quantile regression," Statistics & Probability Letters, Elsevier, vol. 54(4), pages 437-447, October.
    2. Yue, Yu Ryan & Rue, Håvard, 2011. "Bayesian inference for additive mixed quantile regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 84-96, January.
    3. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    4. Dries F. Benoit & Dirk Van den Poel, 2012. "Binary quantile regression: a Bayesian approach based on the asymmetric Laplace distribution," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(7), pages 1174-1188, November.
    5. Alhamzawi, Rahim & Yu, Keming, 2013. "Conjugate priors and variable selection for Bayesian quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 209-219.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Benoit, Dries F. & Van den Poel, Dirk, 2017. "bayesQR: A Bayesian Approach to Quantile Regression," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i07).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Seongil Jo & Taeyoung Roh & Taeryon Choi, 2016. "Bayesian spectral analysis models for quantile regression with Dirichlet process mixtures," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(1), pages 177-206, March.
    2. Karthik Sriram & R. V. Ramamoorthi & Pulak Ghosh, 2016. "On Bayesian Quantile Regression Using a Pseudo-joint Asymmetric Laplace Likelihood," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 78(1), pages 87-104, February.
    3. Dries Benoit & Rahim Alhamzawi & Keming Yu, 2013. "Bayesian lasso binary quantile regression," Computational Statistics, Springer, vol. 28(6), pages 2861-2873, December.
    4. Bernardi, Mauro & Bottone, Marco & Petrella, Lea, 2018. "Bayesian quantile regression using the skew exponential power distribution," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 92-111.
    5. Yunwen Yang & Huixia Judy Wang & Xuming He, 2016. "Posterior Inference in Bayesian Quantile Regression with Asymmetric Laplace Likelihood," International Statistical Review, International Statistical Institute, vol. 84(3), pages 327-344, December.
    6. Yukiko Omata & Hajime Katayama & Toshi. H. Arimura, 2017. "Same concerns, same responses? A Bayesian quantile regression analysis of the determinants for supporting nuclear power generation in Japan," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(3), pages 581-608, July.
    7. Bouoiyour, Jamal & Selmi, Refk & Miftah, Amal, 2015. "“Every cloud has a silver lining”; to what extent does the Arab Spring accelerate the integration among Arab monarchies?," MPRA Paper 70942, University Library of Munich, Germany.
    8. Yuta Kurose & Yasuhiro Omori, 2012. "Bayesian Analysis of Time-Varying Quantiles Using a Smoothing Spline," CIRJE F-Series CIRJE-F-845, CIRJE, Faculty of Economics, University of Tokyo.
    9. Genya Kobayashi & Hideo Kozumi, 2012. "Bayesian analysis of quantile regression for censored dynamic panel data," Computational Statistics, Springer, vol. 27(2), pages 359-380, June.
    10. Alexander Razen & Wolfgang Brunauer & Nadja Klein & Thomas Kneib & Stefan Lang & Nikolaus Umlauf, 2014. "Statistical Risk Analysis for Real Estate Collateral Valuation using Bayesian Distributional and Quantile Regression," Working Papers 2014-12, Faculty of Economics and Statistics, Universität Innsbruck.
    11. Xianhua Dai & Wolfgang Karl Härdle & Keming Yu, 2016. "Do maternal health problems influence child's worrying status? Evidence from the British Cohort Study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(16), pages 2941-2955, December.
    12. Ali Aghamohammadi, 2018. "Bayesian analysis of dynamic panel data by penalized quantile regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 91-108, March.
    13. 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.
    14. Rahim Alhamzawi & Haithem Taha Mohammad Ali, 2020. "Brq: an R package for Bayesian quantile regression," METRON, Springer;Sapienza Università di Roma, vol. 78(3), pages 313-328, December.
    15. Xiaowen Dai & Libin Jin & Lei Shi, 2023. "Quantile regression in random effects meta-analysis model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 469-492, June.
    16. Elisabeth Waldmann & Thomas Kneib & Yu Ryan Yu & Stefan Lang, 2012. "Bayesian semiparametric additive quantile regression," Working Papers 2012-06, Faculty of Economics and Statistics, Universität Innsbruck.
    17. Maria Marino & Alessio Farcomeni, 2015. "Linear quantile regression models for longitudinal experiments: an overview," METRON, Springer;Sapienza Università di Roma, vol. 73(2), pages 229-247, August.
    18. Kneib, Thomas & Silbersdorff, Alexander & Säfken, Benjamin, 2023. "Rage Against the Mean – A Review of Distributional Regression Approaches," Econometrics and Statistics, Elsevier, vol. 26(C), pages 99-123.
    19. David Kohns & Tibor Szendrei, 2020. "Horseshoe Prior Bayesian Quantile Regression," Papers 2006.07655, arXiv.org, revised Mar 2021.
    20. Oh, Man-Suk & Park, Eun Sug & So, Beong-Soo, 2016. "Bayesian variable selection in binary quantile regression," Statistics & Probability Letters, Elsevier, vol. 118(C), pages 177-181.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:107:y:2015:i:c:p:18-26. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.