Quantile regression of ultra-high dimensional partially linear varying-coefficient model with missing observations

Cites Work

Unnamed Item
Unnamed Item
Penalized empirical likelihood for high-dimensional partially linear varying coefficient model with measurement errors
Statistics for high-dimensional data. Methods, theory and applications.
Semi-varying coefficient models with a diverging number of components
Quantile regression and its empirical likelihood with missing response at random
Quantile regression for dynamic partially linear varying coefficient time series models
Empirical likelihood for a varying coefficient partially linear model with diverging number of parameters
Profile likelihood inferences on semiparametric varying-coefficient partially linear models
One-step sparse estimates in nonconcave penalized likelihood models
Quantile regression in partially linear varying coefficient models
Additive regression and other nonparametric models
Convex analysis approach to d. c. programming: Theory, algorithms and applications
Correlation rank screening for ultrahigh-dimensional survival data
Quantile regression for partially linear varying-coefficient model with censoring indicators missing at random
Robust variable selection in high-dimensional varying coefficient models based on weighted composite quantile regression
Feature screening in ultrahigh-dimensional partially linear models with missing responses at random
Local asymptotics for regression splines and confidence regions
Adaptive penalized quantile regression for high dimensional data
Penalized profile least squares-based statistical inference for varying coefficient partially linear errors-in-variables models
Penalized weighted composite quantile regression for partially linear varying coefficient models with missing covariates
Spline estimator for ultra-high dimensional partially linear varying coefficient models
Sparse high-dimensional semi-nonparametric quantile regression in a reproducing kernel Hilbert space
\(\ell_1\)-penalized quantile regression in high-dimensional sparse models
New efficient estimation and variable selection methods for semiparametric varying-coefficient partially linear models
Bayesian empirical likelihood of quantile regression with missing observations
Local Asymptotics for B-Spline Estimators of the Varying Coefficient Model
Statistical Inference in Partially Linear Varying-Coefficient Models with Missing Responses at Random
Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
Quantile regression for robust estimation and variable selection in partially linear varying-coefficient models
Quantile Regression for Analyzing Heterogeneity in Ultra-High Dimension
B-spline estimation for partially linear varying coefficient composite quantile regression models
Statistical inference for varying-coefficient partially linear errors-in-variables models with missing data
Empirical likelihood in varying-coefficient quantile regression with missing observations
Partially linear additive quantile regression in ultra-high dimension
SCAD‐penalized quantile regression for high‐dimensional data analysis and variable selection

This page was built for publication: Quantile regression of ultra-high dimensional partially linear varying-coefficient model with missing observations