Pseudo‐empirical Bayes estimation of small area means based on James–Stein estimation in linear regression models with functional measurement error

DOI10.1002/CJS.11245zbMath1328.62138OpenAlexW1902203376MaRDI QIDQ5256381

Elaheh Torkashvand, Mohammad Jafari Jozani, Mahmoud Torabi

Publication date: 22 June 2015

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

Full work available at URL: https://doi.org/10.1002/cjs.11245

zbMATH Keywords

empirical BayesJames-Stein estimatorsmall area estimationmean squared prediction errorJackknife method

Mathematics Subject Classification ID

Point estimation (62F10) Parametric inference under constraints (62F30) Minimax procedures in statistical decision theory (62C20)

Related Items (2)

Constrained Bayes estimation in small area models with functional measurement error ⋮ Small area estimation under a semi‐parametric covariate measured with error

Cites Work

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• Small area estimation when auxiliary information is measured with error
• Pseudo-empirical Bayes estimation of small area means under a nested error linear regression model with functional measurement errors
• A unified jackknife theory for empirical best prediction with \(M\)-estimation
• Empirical Bayes estimation in finite population sampling under functional measurement error models
• SMALL AREA ESTIMATION USING SURVEY WEIGHTS WITH FUNCTIONAL MEASUREMENT ERROR IN THE COVARIATE
• Empirical and Hierarchical Bayesian Estimation in Finite Population Sampling under Structural Measurement Error Models
• Data Analysis Using Stein's Estimator and its Generalizations
• Flexible Parametric Measurement Error Models
• Multiple roots of estimating functions
• Limiting the Risk of Bayes and Empirical Bayes Estimators--Part II: The Empirical Bayes Case

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