The Annals of Statistics

A Class of Nonlinear Admissible Estimators in the One-Parameter Exponential Family

Dan Ralescu and Stefan Ralescu

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We are concerned with the admissibility of nonlinear estimators of the form $(aX + b)/(cX + d)$ in the one-parameter exponential family, in estimating $g(\theta)$ with quadratic loss. Our method will be reminiscent of that of Karlin who gave sufficient conditions for admissibility of linear estimators $aX$ in estimating the mean in the one-parameter family. Our results generalize those of Ghosh and Meeden who studied admissibility of $aX + b$ for estimating an arbitrary function $g(\theta)$. Particular cases of estimators of the form, $c/X$ are studied and several examples are given. We show that $(n - 2)/(X + a), a \geq 0$ is admissible in estimating the parameter of an exponential density. We also discuss the case of truncated parameter space.

Article information

Ann. Statist., Volume 9, Number 1 (1981), 177-183.

First available in Project Euclid: 12 April 2007

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Zentralblatt MATH identifier


Primary: 62C15: Admissibility
Secondary: 62F10: Point estimation

Nonlinear admissible estimators quadratic loss formal Bayes estimators scale parameter truncated parameter space


Ralescu, Dan; Ralescu, Stefan. A Class of Nonlinear Admissible Estimators in the One-Parameter Exponential Family. Ann. Statist. 9 (1981), no. 1, 177--183. doi:10.1214/aos/1176345344.

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