Adjusted empirical likelihood estimation of distribution function and quantile with nonignorable missing data

DOI10.1007/s11424-018-6334-6zbMath1401.93192OpenAlexW2792822583MaRDI QIDQ1794307

Xianwen Ding, Nian Sheng Tang

Publication date: 15 October 2018

Published in: Journal of Systems Science and Complexity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11424-018-6334-6

zbMATH Keywords

quantilenonignorable missing datadistribution estimationadjusted empirical likelihoodexponential tilting model

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10) System structure simplification (93B11)

Related Items

Dimension-reduced semiparametric estimation of distribution functions and quantiles with nonignorable nonresponse ⋮ Dimension-reduced empirical likelihood estimation and inference for M-estimators with nonignorable nonresponse ⋮ Regularized quantile regression for ultrahigh-dimensional data with nonignorable missing responses ⋮ Estimators for ROC curves with missing biomarkers values and informative covariates ⋮ Robust estimation of generalized estimating equations with finite mixture correlation matrices and missing covariates at random for longitudinal data

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