Quantile regression and variable selection for the single-index model

DOI10.1080/02664763.2014.881786OpenAlexW2126573510MaRDI QIDQ5128663

Ri-quan Zhang, Ji-cai Liu, Weihua Zhao, Yazhao Lv

Publication date: 28 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2014.881786

zbMATH Keywords

quantile regressionvariable selectionoracle propertysingle-index modeladaptive Lasso

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Nonparametric estimation (62G05)

Related Items (10)

Quantile regression for single-index-coefficient regression models ⋮ Composite quantile regression and variable selection in single-index coefficient model ⋮ Sampling Lasso quantile regression for large-scale data ⋮ A weighted quantile regression for nonlinear models with randomly censored data ⋮ Bayesian nonparametric modelling of the link function in the single-index model using a Bernstein–Dirichlet process prior ⋮ Variable selection in the single-index quantile regression model with high-dimensional covariates ⋮ Estimation and variable selection in single-index composite quantile regression ⋮ Quantile regression and variable selection for partially linear model with randomly truncated data ⋮ Weighted composite quantile regression for single index model with missing covariates at random ⋮ Single-index quantile regression with left truncated data

Cites Work

• Unnamed Item
• Unnamed Item
• Single-index quantile regression
• The Adaptive Lasso and Its Oracle Properties
• Penalized least squares for single index models
• Variable selection in a class of single-index models
• Bayesian estimation and variable selection for single index models
• On average derivative quantile regression
• Variable selection in high-dimensional partially linear additive models for composite quantile regression
• Limiting distributions for \(L_1\) regression estimators under general conditions
• On the asymptotics of constrained \(M\)-estimation
• New efficient estimation and variable selection methods for semiparametric varying-coefficient partially linear models
• Semi-parametric estimation of partially linear single-index models
• Single-index model selections
• A SINGLE-INDEX QUANTILE REGRESSION MODEL AND ITS ESTIMATION
• An Effective Bandwidth Selector for Local Least Squares Regression
• Investigating Smooth Multiple Regression by the Method of Average Derivatives
• Variable selection for the single-index model
• Unified LASSO Estimation by Least Squares Approximation
• Weak and strong uniform consistency of kernel regression estimates
• Sliced Inverse Regression for Dimension Reduction
• On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
• Regression Quantiles
• Generalized Partially Linear Single-Index Models
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• An Adaptive Estimation of Dimension Reduction Space
• Regularization and Variable Selection Via the Elastic Net
• An analysis of variance test for normality (complete samples)

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