Estimating linear functionals in nonlinear regression with responses missing at random

DOI10.1214/08-AOS642zbMath1173.62052arXiv0908.3102MaRDI QIDQ834338

Ursula U. Müller

Publication date: 19 August 2009

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0908.3102

zbMATH Keywords

semiparametric regressioninfluence functiongradientconfidence intervalempirical likelihoodweighted empirical estimator

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Censored data models (62N01) General nonlinear regression (62J02)

Related Items

An equivalence result for moment equations when data are missing at random ⋮ Semiparametric fractional imputation using empirical likelihood in survey sampling ⋮ Empirical likelihood semiparametric nonlinear regression analysis for longitudinal data with responses missing at random ⋮ Partially linear varying coefficient models with missing at random responses ⋮ Estimation in semiparametric models with missing data ⋮ The efficiency of the second-order nonlinear least squares estimator and its extension ⋮ Semi-parametric rank regression with missing responses ⋮ Estimators for ROC curves with missing biomarkers values and informative covariates ⋮ Estimating the density of a possibly missing response variable in nonlinear regression ⋮ General \(M\)-estimator processes and their \(m\) out of \(n\) bootstrap with functional nuisance parameters ⋮ On density and regression estimation with incomplete data ⋮ Efficient parameter estimation in regression with missing responses ⋮ Efficient estimation in a regression model with missing responses ⋮ Inference about the slope in linear regression: an empirical likelihood approach ⋮ The signed-rank estimator for nonlinear regression with responses missing at random ⋮ Kernel regression estimation for incomplete data with applications ⋮ Plug-in marginal estimation under a general regression model with missing responses and covariates ⋮ Robust inference for nonlinear regression models ⋮ Nonparametric regression with responses missing at random ⋮ The transfer principle: a tool for complete case analysis ⋮ Semiparametric \(M\)-estimation with non-smooth criterion functions ⋮ SEMIPARAMETRIC EFFICIENCY BOUNDS FOR CONDITIONAL MOMENT RESTRICTION MODELS WITH DIFFERENT CONDITIONING VARIABLES ⋮ Robust location estimators in regression models with covariates and responses missing at random ⋮ Empirical likelihood confidence regions for the parameters of a two phases nonlinear model with and without missing response data ⋮ Efficient estimators for expectations in nonlinear parametric regression models with responses missing at random ⋮ Robust location estimation with missing data ⋮ Empirical likelihood for nonlinear models with missing responses ⋮ Efficiently estimating the error distribution in nonparametric regression with responses missing at random ⋮ Asymptotic properties of semiparametric \(M\)-estimators with multiple change points

Uses Software

• BayesDA

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Weighted least squares estimators in possibly misspecified nonlinear regression
• Empirical likelihood for estimating equations with missing values
• A note on the construction of asymptotically linear estimators
• On adaptive estimation
• On efficient estimation in regression models
• Likelihood-based imputation inference for mean functionals in the presence of missing responses
• Empirical likelihood-based inference under imputation for missing response data
• Semiparametric efficiency in GMM models with auxiliary data
• Semiparametric theory and missing data.
• Partially linear models with missing response variables and error-prone covariates
• ADAPTIVE ESTIMATION IN LINEAR REGRESSION
• Empirical likelihood ratio confidence intervals for a single functional
• Inference based on regression estimator in double sampling
• Nonparametric Estimation of Mean Functionals with Data Missing at Random
• On the construction of efficient estimators in semiparametric models
• Empirical likelihood for linear regression models under imputation for missing responses
• Efficient Estimation of Population-Level Summaries in General Semiparametric Regression Models
• Semiparametric Regression Analysis With Missing Response at Random