New bayesian single index quantile regression based on uniform scale mixture
Joint Authors
al-Alaq, Samir
al-Shaibawi, Taha
Source
Journal of al-Qadisiyah for Pure Science
Issue
Vol. 24, Issue 4 (31 Dec. 2019), pp.9-23, 15 p.
Publisher
al-Qadisiyah University College of Science
Publication Date
2019-12-31
Country of Publication
Iraq
No. of Pages
15
Main Subjects
Abstract EN
To scale back the dimensionality while holding a lot of flexibility of a nonparametric model Wu, et al.
(2010) proposed a single index conditional quantile regression model.
In this paper, a new Bayesian lasso for single index quantile regression model is proposed based on a scale mixture uniform.
In addition, we construct an efficient and sampling Gibbs algorithm for posterior inference based on a uniform scale mixture representation for Laplace distribution.
Simulation study have considered to evaluate our proposed method compare to the existing methods.
The results of simulations indicate that the new Bayesian algorithm performs well.
American Psychological Association (APA)
al-Alaq, Samir& al-Shaibawi, Taha. 2019. New bayesian single index quantile regression based on uniform scale mixture. Journal of al-Qadisiyah for Pure Science،Vol. 24, no. 4, pp.9-23.
https://search.emarefa.net/detail/BIM-1079518
Modern Language Association (MLA)
al-Alaq, Samir& al-Shaibawi, Taha. New bayesian single index quantile regression based on uniform scale mixture. Journal of al-Qadisiyah for Pure Science Vol. 24, no. 4 (2019), pp.9-23.
https://search.emarefa.net/detail/BIM-1079518
American Medical Association (AMA)
al-Alaq, Samir& al-Shaibawi, Taha. New bayesian single index quantile regression based on uniform scale mixture. Journal of al-Qadisiyah for Pure Science. 2019. Vol. 24, no. 4, pp.9-23.
https://search.emarefa.net/detail/BIM-1079518
Data Type
Journal Articles
Language
English
Notes
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Record ID
BIM-1079518