Adaptive structure inferences on partially linear error-in-function models with error-prone covariates

DOI10.1007/s42952-019-00012-0zbMath1485.62055OpenAlexW3000594852MaRDI QIDQ2131894

Ziyi Ye, Haiying Ding, Zhen-Sheng Huang

Publication date: 27 April 2022

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s42952-019-00012-0

zbMATH Keywords

generalized likelihood ratio testWilks phenomenonprofile least-square methodserror-prone covariatespartially linear error-in-function models

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20)

Uses Software

• SemiPar

Cites Work

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• Estimation and inference of error-prone covariate effect in the presence of confounding variables
• Empirical likelihood for the parametric part in partially linear errors-in-function models
• Tests for nonparametric parts on partially linear single index models
• Estimation in partially linear models and numerical comparisons
• Bootstrap approximation of wavelet estimates in a semiparametric regression model
• Statistical inference for semiparametric varying-coefficient partially linear models with error-prone linear covariates
• A central limit theorem for generalized quadratic forms
• Nonparametric regression with errors in variables
• On parameter estimation for semi-linear errors-in-variables models
• Testing structural change in partially linear single-index models with error-prone linear covariates
• Generalized likelihood ratio statistics and Wilks phenomenon
• SIMEX and standard error estimation in semiparametric measurement error models
• Asymptotic normality of parametric part in partially linear models with measurement error in the nonparametric part
• Empirical likelihood for partly linear models with errors in all variables
• Generalized varying coefficient partially linear measurement errors models
• Testing the suitability of polynomial models in errors-in-variables problems
• Variable selection in semiparametric regression modeling
• Nonparametric inference with generalized likelihood ratio tests (With comments and rejoinder)
• PARTIALLY LINEAR MODEL SELECTION BY THE BOOTSTRAP
• Empirical likelihood inference for parameters in a partially linear errors-in-variables model
• Empirical Likelihood Confidence Region for Parameters in Semi-linear Errors-in-Variables Models
• Locally Efficient Estimators for Semiparametric Models With Measurement Error
• Partially linear models with missing response variables and error-prone covariates
• Conditional bootstrap methods in the mean-shift model
• The Analysis of Categorical Data From Complex Sample Surveys: Chi-Squared Tests for Goodness of Fit and Independence in Two-Way Tables
• Generalized Partially Linear Single-Index Models
• Semiparametric Regression
• Statistical estimation for partially linear error-in-variable models with error-prone covariates
• A Semi‐parametric Regression Model with Errors in Variables
• Locally efficient semiparametric estimators for a class of Poisson models with measurement error
• Statistical inference for varying-coefficient models with error-prone covariates
• Variable Selection in Nonparametric Varying-Coefficient Models for Analysis of Repeated Measurements
• Generalized likelihood ratio tests for the structure of semiparametric additive models
• Measurement Error in Nonlinear Models
• Nonparametric Inferences for Additive Models

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