Bayesian analysis of penalized quantile regression for longitudinal data

DOI10.1007/s00362-015-0737-4zbMath1416.62206OpenAlexW2205486885MaRDI QIDQ1685287

Peng Zhang

Publication date: 13 December 2017

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-015-0737-4

zbMATH Keywords

longitudinal datarandom effectspenalty methodsasymmetric Laplace distributionhierarchical modelsBayesian quantile regression

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Bayesian inference (62F15)

Related Items (10)

A Bayesian conditional model for bivariate mixed ordinal and skew continuous longitudinal responses using quantile regression ⋮ Shrinkage estimation of fixed and random effects in linear quantile mixed models ⋮ Bayesian LASSO-Regularized quantile regression for linear regression models with autoregressive errors ⋮ Quantile regression in random effects meta-analysis model ⋮ Bayesian empirical likelihood of quantile regression with missing observations ⋮ Bayesian analysis of dynamic panel data by penalized quantile regression ⋮ Bayesian quantile regression for analyzing ordinal longitudinal responses in the presence of non-ignorable missingness ⋮ Bayesian bridge-randomized penalized quantile regression for ordinal longitudinal data, with application to firm's bond ratings ⋮ Constrained Bayesian doubly elastic net Lasso for linear quantile mixed models ⋮ Quantile regression for nonlinear mixed effects models: a likelihood based perspective

Uses Software

• R

Cites Work

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