Bayesian adaptive Lasso for quantile regression models with nonignorably missing response data

DOI10.1080/03610918.2018.1468452OpenAlexW2910640044WikidataQ128594732 ScholiaQ128594732MaRDI QIDQ5087547

Nian Sheng Tang, Deng-Ke Xu

Publication date: 1 July 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2018.1468452

zbMATH Keywords

Gibbs samplerMetropolis-Hastings algorithmnonignorable missing dataBayesian adaptive Lasso

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (2)

Empirical likelihood in varying-coefficient quantile regression with missing observations ⋮ Bayesian empirical likelihood of quantile regression with missing observations

Cites Work

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