Statistical inference on restricted linear regression models with partial distortion measurement errors
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Publication:318978
DOI10.1214/15-BJPS289zbMath1381.62233MaRDI QIDQ318978
Jun Zhang, Yongbin Fan, Zheng-Hong Wei
Publication date: 6 October 2016
Published in: Brazilian Journal of Probability and Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.bjps/1469807222
Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05) Nonparametric estimation (62G05) Hypothesis testing in multivariate analysis (62H15) Bootstrap, jackknife and other resampling methods (62F40)
Related Items (6)
General least product relative error estimation for multiplicative regression models with or without multiplicative distortion measurement errors ⋮ Linear regression models with general distortion measurement errors ⋮ Logarithmic calibration for multiplicative distortion measurement errors regression models ⋮ Kernel density estimation for multiplicative distortion measurement regression models ⋮ Absolute logarithmic calibration for correlation coefficient with multiplicative distortion ⋮ Statistical estimation for single-index varying-coefficient models with multiplicative distortion measurement errors
Cites Work
- Unnamed Item
- Unnamed Item
- A CONSISTENT DIAGNOSTIC TEST FOR REGRESSION MODELS USING PROJECTIONS
- Nonparametric checks for varying coefficient models with missing response at random
- A ridge regression estimation approach to the measurement error model
- A revisit to correlation analysis for distortion measurement error data
- Nonlinear models with measurement errors subject to single-indexed distortion
- On a dimension reduction regression with covariate adjustment
- Partial covariate adjusted regression
- Estimation in covariate-adjusted regression
- Statistical inference for semiparametric varying-coefficient partially linear models with error-prone linear covariates
- Checking the adequacy for a distortion errors-in-variables parametric regression model
- Jackknife, bootstrap and other resampling methods in regression analysis
- Partial linear single index models with distortion measurement errors
- Testing the adequacy of varying coefficient models with missing responses at random
- Statistical inference on restricted partially linear additive errors-in-variables models
- Profile inference on partially linear varying-coefficient errors-in-variables models under restricted condition
- Variable selection for covariate adjusted regression model
- Frontier estimation in the presence of measurement error with unknown variance
- Nonparametric check for partial linear errors-in-covariables models with validation data
- Covariate-adjusted nonlinear regression
- Empirical likelihood of varying coefficient errors-in-variables models with longitudinal data
- Nonlinear measurement error models subject to additive distortion
- Inference for covariate adjusted regression via varying coefficient models
- Estimation and variable selection in partial linear single index models with error-prone linear covariates
- Covariate-adjusted linear mixed effects model with an application to longitudinal data
- Covariate-Adjusted Partially Linear Regression Models
- Empirical Likelihood Confidence Region for the Parameter in a Partially Linear Errors-in-Variables Model
- Bootstrap Approximations in Model Checks for Regression
- Weak and strong uniform consistency of kernel regression estimates
- Generalized Partially Linear Single-Index Models
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Variable Selection in Nonparametric Classification Via Measurement Error Model Selection Likelihoods
- Variable Selection for Partially Linear Models With Measurement Errors
- Covariate Adjusted Correlation Analysis via Varying Coefficient Models
- Measurement Error in Nonlinear Models
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