Variable selection and weighted composite quantile estimation of regression parameters with left-truncated data

DOI10.1080/03610926.2017.1376089OpenAlexW2753040372MaRDI QIDQ5154093

Lu Lin, Mei Yao, Jiang-Feng Wang, Yu-Xin Wang

Publication date: 1 October 2021

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2017.1376089

zbMATH Keywords

asymptotic normalityvariable selectionoracle propertycomposite quantile regressionleft-truncated data

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05) Estimation in survival analysis and censored data (62N02)

Related Items (1)

Single-index quantile regression with left truncated data

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