Calibration procedures for linear regression models with multiplicative distortion measurement errors

DOI10.1214/19-BJPS451zbMath1445.62182MaRDI QIDQ783272

Yan Zhou, Jun Zhang

Publication date: 12 August 2020

Published in: Brazilian Journal of Probability and Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.bjps/1595232025

zbMATH Keywords

confidence intervalscalibrationleast squares estimatormeasurement errorslocal linear smoothingmultiplicative distortion

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Nonparametric tolerance and confidence regions (62G15)

Related Items (6)

Measurement errors models with exponential parametric multiplicative distortions ⋮ Estimation of correlation coefficient with general distortion measurement errors ⋮ Kernel density estimation for multiplicative distortion measurement regression models ⋮ Absolute logarithmic calibration for correlation coefficient with multiplicative distortion ⋮ Nonlinear multiplicative distortion regression models with second-order estimation ⋮ Logarithmic calibration for nonparametric multiplicative distortion measurement errors models

Cites Work

• Unnamed Item
• Unnamed Item
• Nonparametric covariate-adjusted regression
• Empirical likelihood confidence intervals for nonparametric functional data analysis
• A nonparametric test for covariate-adjusted models
• Empirical likelihood for a partially linear model with covariate data missing at random
• Empirical likelihood for a varying coefficient partially linear model with diverging number of parameters
• Partial covariate adjusted regression
• SIMEX estimation for single-index model with covariate measurement error
• Covariate-adjusted nonlinear regression
• A goodness-of-fit test for variable-adjusted models
• Inference for covariate adjusted regression via varying coefficient models
• The Empirical Likelihood Goodness-of-Fit Test for a Regression Model with Randomly Censored Data
• Covariate-adjusted linear mixed effects model with an application to longitudinal data
• Multicovariate-adjusted regression models
• Empirical Likelihood‐Based Inferences for Generalized Partially Linear Models
• Covariate-Adjusted Partially Linear Regression Models
• A heteroscedastic measurement error model based on skew and heavy-tailed distributions with known error variances
• Nonlinear regression models with general distortion measurement errors
• Empirical likelihood for single index model with missing covariates at random
• Covariate Adjusted Correlation Analysis via Varying Coefficient Models
• Correlation curve estimation for multiplicative distortion measurement errors data
• Local linear estimation for covariate-adjusted varying-coefficient models

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