Institute of Mathematical Statistics Lecture Notes - Monograph Series

A note on the $U, V$ method of estimation

Arthur Cohen and Harold Sackrowitz

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Abstract

The $U, V$ method of estimation provides unbiased estimators or predictors of random quantities. The method was introduced by Robbins and subsequently studied in a series of papers by Robbins and Zhang. (See Zhang). Practical applications of the method are featured in these papers. We demonstrate that for one $U$ function (one for which there is an important application) the $V$ estimator is inadmissible for a wide class of loss functions. For another important $U$ function the $V$ estimator is admissible for the squared error loss function.

Chapter information

Source
Regina Liu, William Strawderman and Cun-Hui Zhang, eds., Complex Datasets and Inverse Problems: Tomography, Networks and Beyond (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2007), 172-176

Dates
First available in Project Euclid: 4 December 2007

Permanent link to this document
https://projecteuclid.org/euclid.lnms/1196794951

Digital Object Identifier
doi:10.1214/074921707000000139

Subjects
Primary: 62C15: Admissibility
Secondary: 62F15: Bayesian inference

Keywords
admissibility unbiased estimators asymptotic efficiency

Rights
Copyright © 2007, Institute of Mathematical Statistics

Citation

Cohen, Arthur; Sackrowitz, Harold. A note on the $U, V$ method of estimation. Complex Datasets and Inverse Problems, 172--176, Institute of Mathematical Statistics, Beachwood, Ohio, USA, 2007. doi:10.1214/074921707000000139. https://projecteuclid.org/euclid.lnms/1196794951


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