Flexible Bayesian quantile regression based on the generalized asymmetric Huberised-type distribution
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11222-024-10453-1.pdf
Reference42 articles.
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3. Alhamzawi, R., Yu, K.: Conjugate priors and variable selection for Bayesian quantile regression. Comput. Stat. Data Anal. 64, 209–219 (2013). https://doi.org/10.1016/j.csda.2012.01.014
4. Alhamzawi, R., Yu, K., Benoit, D.F.: Bayesian adaptive Lasso quantile regression. Stat. Model. 12(3), 279–297 (2012). https://doi.org/10.1177/1471082X1101200304
5. Alhamzawi, R., Alhamzawi, A., Ali, H.T.M.: New Gibbs sampling methods for bayesian regularized quantile regression. Comput. Biol. Med. 110, 52–65 (2019). https://doi.org/10.1016/j.compbiomed.2019.05.011
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