Variable selection in quantile regression via Gibbs sampling

DOI10.1080/02664763.2011.620082OpenAlexW2030579408MaRDI QIDQ5126988

Rahim Alhamzawi, Ke-ming Yu

Publication date: 21 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2011.620082

zbMATH Keywords

quantile regressionGibbs samplerprior distributionskewed Laplace distribution

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (19)

Bayesian variable selection in quantile regression with random effects: an application to Municipal Human Development Index ⋮ Bayesian variable selection in binary quantile regression ⋮ Bayesian model selection in ordinal quantile regression ⋮ Bayesian quantile regression using the skew exponential power distribution ⋮ Handling multicollinearity in quantile regression through the use of principal component regression ⋮ Bayesian quantile regression and variable selection for partial linear single-index model: Using free knot spline ⋮ Bayesian Approaches to Shrinkage and Sparse Estimation ⋮ Model selection in quantile regression models ⋮ Bayesian variable selection and estimation in maximum entropy quantile regression ⋮ Bayesian quantile regression analysis for continuous data with a discrete component at zero ⋮ A non-iterative posterior sampling algorithm for linear quantile regression model ⋮ Bayesian variable selection in quantile regression using the Savage-Dickey density ratio ⋮ An efficient algorithm for structured sparse quantile regression ⋮ Elastic net penalized quantile regression model ⋮ Bayesian regularized quantile structural equation models ⋮ Research on regional differences and influencing factors of green technology innovation efficiency of China's high-tech industry ⋮ Bayesian quantile regression for hierarchical linear models ⋮ Bayesian analysis for zero-or-one inflated proportion data using quantile regression ⋮ Bayesian empirical likelihood and variable selection for censored linear model with applications to acute myelogenous leukemia data

Uses Software

• factorQR

Cites Work

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