Weighted least squares estimation with missing responses: an empirical likelihood approach

DOI10.1214/13-EJS793zbMath1336.62092OpenAlexW2083557910MaRDI QIDQ1951142

Anton Schick

Publication date: 29 May 2013

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

Full work available at URL: https://projecteuclid.org/euclid.ejs/1364994253

zbMATH Keywords

efficiencymissing at randommaximum empirical likelihood estimationestimated constraintsheteroscedastic linear regressionincreasing number of constraints

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05) Nonparametric estimation (62G05)

Related Items (3)

Efficiency for heteroscedastic regression with responses missing at random ⋮ Some probability inequalities of least-squares estimator in non linear regression model with strong mixing errors ⋮ Inference about the slope in linear regression: an empirical likelihood approach

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• Asymptotically Efficient Estimation in the Presence of Heteroskedasticity of Unknown Form

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