Single-index composite quantile regression with heteroscedasticity and general error distributions

DOI10.1007/s00362-014-0646-yzbMath1370.62023OpenAlexW2094146877MaRDI QIDQ259677

Rong Jiang, Zhan-Gong Zhou, Wei-Min Qian

Publication date: 18 March 2016

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

Full work available at URL: https://doi.org/10.1007/s00362-014-0646-y

zbMATH Keywords

asymptotic efficiencycomposite quantile regressioncompsite quantile regression (CQR)single-index modelweighted CQR (WCQR)

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)

Related Items (14)

Weighted composite quantile regression for single-index models ⋮ Joint estimation for single index mean-covariance models with longitudinal data ⋮ Regression estimation via information-weighted composite models with different dimensions ⋮ Block average quantile regression for massive dataset ⋮ Composite quantile regression for massive datasets ⋮ High-dimensional local polynomial regression with variable selection and dimension reduction ⋮ Renewable composite quantile method and algorithm for nonparametric models with streaming data ⋮ Single-index composite quantile regression for massive data ⋮ Weighted composite quantile regression for partially linear varying coefficient models ⋮ Robust communication-efficient distributed composite quantile regression and variable selection for massive data ⋮ Quantile regression in varying-coefficient models: non-crossing quantile curves and heteroscedasticity ⋮ Robust and efficient estimating equations for longitudinal data partial linear models and its applications ⋮ Robust estimation of single index models with responses missing at random ⋮ Optimal subsampling for composite quantile regression in big data

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