Robust empirical likelihood for partially linear models via weighted composite quantile regression
From MaRDI portal
Publication:1643001
DOI10.1007/s00180-018-0793-zzbMath1417.62107OpenAlexW2784404164MaRDI QIDQ1643001
Publication date: 18 June 2018
Published in: Computational Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00180-018-0793-z
Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35) Nonparametric estimation (62G05)
Related Items (2)
A new orthogonality empirical likelihood for varying coefficient partially linear instrumental variable models with longitudinal data ⋮ Imputation-based empirical likelihood inferences for partially nonlinear quantile regression models with missing responses
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Weighted composite quantile regression for single-index models
- Penalized weighted composite quantile regression in the linear regression model with heavy-tailed autocorrelated errors
- Imputation based statistical inference for partially linear quantile regression models with missing responses
- Empirical likelihood for quantile regression models with longitudinal data
- Empirical likelihood ratio confidence regions
- Composite quantile regression and the oracle model selection theory
- Empirical likelihood for linear models with missing responses
- Estimation in a semiparametric partially linear errors-in-variables model
- Empirical likelihood for partly linear models with errors in all variables
- Empirical likelihood for composite quantile regression modeling
- QR decomposition based orthogonality estimation for partially linear models with longitudinal data
- Weighted composite quantile regression estimation and variable selection for varying coefficient models with heteroscedasticity
- Partially linear models with missing response variables and error-prone covariates
- Empirical Likelihood Inferences for Semiparametric Varying-Coefficient Partially Linear Models with Longitudinal Data
- Empirical Likelihood Semiparametric Regression Analysis for Longitudinal Data
- Penalized Composite Quasi-Likelihood for Ultrahigh Dimensional Variable Selection
- Weighted composite quantile regression estimation of DTARCH models
- Focused information criterion and model averaging based on weighted composite quantile regression
- New Estimation and Model Selection Procedures for Semiparametric Modeling in Longitudinal Data Analysis
This page was built for publication: Robust empirical likelihood for partially linear models via weighted composite quantile regression
