Variable selection for additive partial linear quantile regression with missing covariates
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Publication:321935
DOI10.1016/j.jmva.2016.08.009zbMath1348.62148arXiv1510.00094OpenAlexW2418496546MaRDI QIDQ321935
Publication date: 14 October 2016
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1510.00094
Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)
Related Items (9)
An efficient estimation for the parameter in additive partially linear models with missing covariates ⋮ Regularized quantile regression for ultrahigh-dimensional data with nonignorable missing responses ⋮ Empirical likelihood in single-index partially functional linear model with missing observations ⋮ Variable selection for nonparametric quantile regression via measurement error model ⋮ Bayesian empirical likelihood of quantile regression with missing observations ⋮ An improvement on the efficiency of complete-case-analysis with nonignorable missing covariate data ⋮ Penalized weighted composite quantile regression for partially linear varying coefficient models with missing covariates ⋮ Quantile regression of partially linear single-index model with missing observations ⋮ Two stage smoothing in additive models with missing covariates
Uses Software
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