On attainable Cramer - Rao type lower bounds for weighted loss functions

Piotr W Mikulski and Michael Monsour

Statistics & Probability Letters, 1988, vol. 7, issue 1, 1-2

Abstract: Let Y = (Y1,...,Yn) be any random vector, with density [phi] [gamma] ([gamma], [theta]) where [theta] [epsilon] [Phi] [subset of] R1. Suppose that [phi] is regular. Let g(Y) = - [varpi]2log[phi]/[varpi][theta]2. An attainable lower bound for Eg(Y)([theta]-[theta])2 is developed and an application to the first order autoregressive process is cited.

Keywords: optimality; maximum; likelihood; estimators; weighted; quadratic; loss; efficiency (search for similar items in EconPapers)
Date: 1988
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