Empirical and hierarchical Bayesian estimation in finite population sampling under structural measurement error models

Malay Ghosh; Karabi Sinha; Dalho Kim

doi:10.1111/j.1467-9469.2006.00492.x

Empirical and hierarchical Bayesian estimation in finite population sampling under structural measurement error models

Malay Ghosh, Karabi Sinha, Dalho Kim

Research output: Contribution to journal › Article › peer-review

37 Scopus citations

Abstract

This paper considers simultaneous estimation of means from several strata. A model-based approach is taken, where the covariates in the superpopulation model are subject to measurement errors. Empirical Bayes (EB) and Hierarchical Bayes estimators of the strata means are developed and asymptotic optimality of EB estimators is proved. Their performances are examined and compared with that of the sample mean in a simulation study as well as in data analysis.

Original language	English (US)
Pages (from-to)	591-608
Number of pages	18
Journal	Scandinavian Journal of Statistics
Volume	33
Issue number	3
DOIs	https://doi.org/10.1111/j.1467-9469.2006.00492.x
State	Published - Sep 2006
Externally published	Yes

Keywords

Asymptotic optimality
Bayes risk
Consistency

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1111/j.1467-9469.2006.00492.x

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AB - This paper considers simultaneous estimation of means from several strata. A model-based approach is taken, where the covariates in the superpopulation model are subject to measurement errors. Empirical Bayes (EB) and Hierarchical Bayes estimators of the strata means are developed and asymptotic optimality of EB estimators is proved. Their performances are examined and compared with that of the sample mean in a simulation study as well as in data analysis.

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KW - Bayes risk

KW - Consistency

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Empirical and hierarchical Bayesian estimation in finite population sampling under structural measurement error models

Abstract

Keywords

ASJC Scopus subject areas

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