Efficient parameter estimation in regression with missing responses

DOI10.1214/12-EJS708zbMath1295.62022MaRDI QIDQ1950854

Ursula U. Müller, Ingrid Van Keilegom

Publication date: 28 May 2013

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ejs/1340974141

zbMATH Keywords

efficiencyinfluence functionquantile regressionnonlinear regressionmissing at randomnuisance functionparametric regressionquasi-likelihood regression

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric estimation (62G05) General nonlinear regression (62J02)

Related Items (8)

Efficiency for heteroscedastic regression with responses missing at random ⋮ Weighted least squares estimation with missing responses: an empirical likelihood approach ⋮ Inference about the slope in linear regression: an empirical likelihood approach ⋮ A note on improving the efficiency of inverse probability weighted estimator using the augmentation term ⋮ Quantile regression and its empirical likelihood with missing response at random ⋮ SEMIPARAMETRIC EFFICIENCY BOUNDS FOR CONDITIONAL MOMENT RESTRICTION MODELS WITH DIFFERENT CONDITIONING VARIABLES ⋮ Efficient estimators for expectations in nonlinear parametric regression models with responses missing at random ⋮ Model checking for parametric regressions with response missing at random

Cites Work

• Unnamed Item
• Weighted least squares estimators in possibly misspecified nonlinear regression
• Estimating linear functionals in nonlinear regression with responses missing at random
• Estimation of single index model with missing response at random
• Estimation in partially linear models with missing responses at random
• 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
• Asymptotic efficiency in estimation with conditional moment restrictions
• Semiparametric theory and missing data.
• Estimating Equations Inference With Missing Data
• Simulation and the Asymptotics of Optimization Estimators
• Semiparametric efficiency bounds
• ADAPTIVE ESTIMATION IN LINEAR REGRESSION
• Efficiency Bounds for Semiparametric Regression
• Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
• On the construction of efficient estimators in semiparametric models
• Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data
• Estimation of Semiparametric Models when the Criterion Function Is Not Smooth

This page was built for publication: Efficient parameter estimation in regression with missing responses