Double penalized regularization estimation for partially linear instrumental variable models with ultrahigh dimensional instrumental variables
DOI10.1080/03610918.2021.1965166OpenAlexW3199206569MaRDI QIDQ6141683
Xinrong Tang, Weiming Yang, Junqi Wang, Pei Xin Zhao
Publication date: 23 January 2024
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2021.1965166
partially linear modelpenalized estimationendogenous covariateultrahigh dimensional instrumental variable
Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Order statistics; empirical distribution functions (62G30)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Variable selection for partially linear models via partial correlation
- Nearly unbiased variable selection under minimax concave penalty
- Semiparametric variable selection for partially varying coefficient models with endogenous variables
- Assumptions of IV methods for observational epidemiology
- SCAD-penalized regression in high-dimensional partially linear models
- Weak convergence and empirical processes. With applications to statistics
- Regularization statistical inferences for partially linear models with high dimensional endogenous covariates
- QR decomposition based orthogonality estimation for partially linear models with longitudinal data
- Modified SEE variable selection for varying coefficient instrumental variable models
- Nonparametric independence screening for ultra-high dimensional generalized varying coefficient models with longitudinal data
- Endogeneity in high dimensions
- Empirical likelihood inferences for semiparametric instrumental variable models
- Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain
- GMM estimation in partial linear models with endogenous covariates causing an over-identified problem
- Empirical Likelihood Semiparametric Regression Analysis for Longitudinal Data
- Partial Linear Models for Longitudinal Data Based on Quadratic Inference Functions
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Sure Independence Screening for Ultrahigh Dimensional Feature Space
- Empirical likelihood inference in partially linear single-index models with endogenous covariates
- Orthogonal weighted empirical likelihood-based variable selection for semiparametric instrumental variable models
- On the Use of the Lasso for Instrumental Variables Estimation with Some Invalid Instruments
- Variable Selection for Partially Linear Models With Measurement Errors
- Regularization Methods for High-Dimensional Instrumental Variables Regression With an Application to Genetical Genomics
- New Estimation and Model Selection Procedures for Semiparametric Modeling in Longitudinal Data Analysis
This page was built for publication: Double penalized regularization estimation for partially linear instrumental variable models with ultrahigh dimensional instrumental variables
