\(M\)-estimation and quantile estimation in the presence of auxiliary information

DOI10.1016/0378-3758(94)00040-3zbMath0816.62031OpenAlexW1966919947MaRDI QIDQ1347136

Biao Zhang

Publication date: 3 July 1995

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(94)00040-3

zbMATH Keywords

consistencyasymptotic normalityM-estimatorssimulation studyauxiliary informationrelative efficiencyasymptotic variancesquantile estimatorsempirical likelihood technique

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items (18)

Empirical likelihood-based inference in Poisson autoregressive model with conditional moment restrictions ⋮ Quantile Estimation in the Presence of Auxiliary Information under Negatively Associated Samples ⋮ Empirical likelihood confidence intervals for \(M\)-functionals in the presence of auxiliary information ⋮ Dimension-reduced empirical likelihood estimation and inference for M-estimators with nonignorable nonresponse ⋮ An information-theoretic approach to effective inference for Z-functionals ⋮ Asymptotic \(Z\) and chi-squared tests with auxiliary information ⋮ Estimating a distribution function in the presence of auxiliary information ⋮ An empirical likelihood method for semiparametric linear regression with right censored data ⋮ Confidence intervals for a distribution function in the presence of auxiliary information ⋮ Nonparametric estimators of probability characteristics using unbiased prior conditions ⋮ Empirical likelihood-based inference in generalized random coefficient autoregressive model with conditional moment restrictions ⋮ Quantile estimation for discrete data via empirical likelihood ⋮ Conditional quantile estimation with auxiliary information for left-truncated and dependent data ⋮ Efficient M-estimators with auxiliary information ⋮ An estimator of a conditional quantile in the presence of auxiliary information ⋮ Dimension reduction for kernel-assisted M-estimators with missing response at random ⋮ Improved density and distribution function estimation ⋮ Estimating the treatment effect in the two-sample problem with auxiliary information

Cites Work

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• Empirical likelihood ratio confidence regions
• Pseudo-likelihood theory for empirical likelihood
• Empirical likelihood for linear models
• Empirical likelihood and general estimating equations
• Empirical likelihood is Bartlett-correctable
• Empirical likelihood ratio confidence intervals for a single functional
• Empirical likelihood estimation for finite populations and the effective usage of auxiliary information
• Robust Estimation of a Location Parameter

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