Statistics Papers

Document Type

Conference Paper

Date of this Version

1993

Publication Source

Proceedings of Penn State Conference on Multivariate Analysis

Abstract

A bound is given for the Bayes risk of an estimator under truncated squared error loss. The bound derives from an information inequality for the risk under this loss. It is then used to provide new proofs for some classical results of asymptotic theory.

Keywords

Information inequality, cramer-rao inequality, truncated squared error efficiency, local asymptotic minimaxity, superefficiency

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Date Posted: 27 November 2017