The Annals of Statistics

Adaptive Estimators for Simultaneous Estimation of Poisson Means

H. M. Hudson

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Abstract

A new estimator for smoothing towards log-linear models for Poisson means is introduced. The estimator is a generalization of one of Peng (1975). The theoretical basis for the choice of estimator is developed from an approximation to the mean square error of any estimator of Poisson means. The new estimator and its competitors are evaluated in simulations. The method has widespread application in contingency table analysis.

Article information

Source
Ann. Statist., Volume 13, Number 1 (1985), 246-261.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176346590

Digital Object Identifier
doi:10.1214/aos/1176346590

Mathematical Reviews number (MathSciNet)
MR773165

Zentralblatt MATH identifier
0595.62050

JSTOR
links.jstor.org

Subjects
Primary: 62C15: Admissibility

Keywords
Empirical Bayes empty cells $\log$-linear model minimax multinomial multiparameter estimation Poisson random effects estimation Stein estimator

Citation

Hudson, H. M. Adaptive Estimators for Simultaneous Estimation of Poisson Means. Ann. Statist. 13 (1985), no. 1, 246--261. doi:10.1214/aos/1176346590. https://projecteuclid.org/euclid.aos/1176346590


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Corrections

  • See Correction: H. M. Hudson. Correction: Adaptive Estimators for Simultaneous Estimation of Poisson Means. Ann. Statist., Volume 14, Number 1 (1986), 360--360.