Model selection and model averaging for semiparametric partially linear models with missing data

DOI10.1080/03610926.2017.1410717OpenAlexW2776611050MaRDI QIDQ5022780

Jie Zeng, Guozhi Hu, Yao-hua Rong, Wei-hu Cheng

Publication date: 19 January 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2017.1410717

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20)

Related Items

Cross-validation-based model averaging in linear models with response missing at random, A robust model averaging approach for partially linear models with responses missing at random, Optimal model averaging for semiparametric partially linear models with measurement errors, Model selection and model averaging for analysis of truncated and censored data with measurement error

Uses Software

• SemiPar

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Focused vector information criterion model selection and model averaging regression with missing response
• Empirical likelihood for semiparametric regression model with missing response data
• Jackknife model averaging
• Automatic model selection for partially linear models
• Estimation in partially linear models with missing responses at random
• Functional semiparametric partially linear model with autoregressive errors
• Estimating the dimension of a model
• Model averaging for varying-coefficient partially linear measurement error models
• Frequentist model averaging estimation for the censored partial linear quantile regression model
• Focused information criterion and model averaging for generalized additive partial linear models
• Optimal Weight Choice for Frequentist Model Average Estimators
• Focused Information Criteria and Model Averaging for the Cox Hazard Regression Model
• Partially linear models with missing response variables and error-prone covariates
• Information Theory and Mixing Least-Squares Regressions
• Maximum likelihood identification of Gaussian autoregressive moving average models
• Adaptive Regression by Mixing
• Semiparametric Regression
• Frequentist Model Average Estimators
• The Focused Information Criterion
• Focused model selection in quantile regression
• Least Squares Model Averaging
• Semiparametric Regression Analysis With Missing Response at Random