Open Access
December, 1951 Minimum Variance Estimation Without Regularity Assumptions
Douglas G. Chapman, Herbert Robbins
Ann. Math. Statist. 22(4): 581-586 (December, 1951). DOI: 10.1214/aoms/1177729548

Abstract

Following the essential steps of the proof of the Cramer-Rao inequality [1, 2] but avoiding the need to transform coordinates or to differentiate under integral signs, a lower bound for the variance of estimators is obtained which is (a) free from regularity assumptions and (b) at least equal to and in some cases greater than that given by the Cramer-Rao inequality. The inequality of this paper might also be obtained from Barankin's general result [3]. Only the simplest case--that of unbiased estimation of a single real parameter--is considered here but the same idea can be applied to more general problems of estimation.

Citation

Download Citation

Douglas G. Chapman. Herbert Robbins. "Minimum Variance Estimation Without Regularity Assumptions." Ann. Math. Statist. 22 (4) 581 - 586, December, 1951. https://doi.org/10.1214/aoms/1177729548

Information

Published: December, 1951
First available in Project Euclid: 28 April 2007

zbMATH: 0044.34302
MathSciNet: MR44084
Digital Object Identifier: 10.1214/aoms/1177729548

Rights: Copyright © 1951 Institute of Mathematical Statistics

Vol.22 • No. 4 • December, 1951
Back to Top