Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution Specification

In this paper, we are interested in estimating several quantiles simultaneously in a regression context via the Bayesian approach. Assuming that the error term has an asymmetric Laplace distribution and using the relation between two distinct quantiles of this distribution, we propose a simple fully...

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Main Author: Josephine Merhi Bleik
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Journal of Probability and Statistics
Online Access:http://dx.doi.org/10.1155/2019/8610723
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author Josephine Merhi Bleik
author_facet Josephine Merhi Bleik
author_sort Josephine Merhi Bleik
collection DOAJ
description In this paper, we are interested in estimating several quantiles simultaneously in a regression context via the Bayesian approach. Assuming that the error term has an asymmetric Laplace distribution and using the relation between two distinct quantiles of this distribution, we propose a simple fully Bayesian method that satisfies the noncrossing property of quantiles. For implementation, we use Metropolis-Hastings within Gibbs algorithm to sample unknown parameters from their full conditional distribution. The performance and the competitiveness of the underlying method with other alternatives are shown in simulated examples.
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spelling doaj-art-334256cc3bf94f84b7bf1f638f9f0d762025-08-20T02:24:21ZengWileyJournal of Probability and Statistics1687-952X1687-95382019-01-01201910.1155/2019/86107238610723Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution SpecificationJosephine Merhi Bleik0Sorbonne Universités, Université de Technologie de Compiègne, LMAC, Compiègne Cedex, FranceIn this paper, we are interested in estimating several quantiles simultaneously in a regression context via the Bayesian approach. Assuming that the error term has an asymmetric Laplace distribution and using the relation between two distinct quantiles of this distribution, we propose a simple fully Bayesian method that satisfies the noncrossing property of quantiles. For implementation, we use Metropolis-Hastings within Gibbs algorithm to sample unknown parameters from their full conditional distribution. The performance and the competitiveness of the underlying method with other alternatives are shown in simulated examples.http://dx.doi.org/10.1155/2019/8610723
spellingShingle Josephine Merhi Bleik
Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution Specification
Journal of Probability and Statistics
title Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution Specification
title_full Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution Specification
title_fullStr Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution Specification
title_full_unstemmed Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution Specification
title_short Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution Specification
title_sort fully bayesian estimation of simultaneous regression quantiles under asymmetric laplace distribution specification
url http://dx.doi.org/10.1155/2019/8610723
work_keys_str_mv AT josephinemerhibleik fullybayesianestimationofsimultaneousregressionquantilesunderasymmetriclaplacedistributionspecification