Authors

Kamel Rekab

Document Type

Article

Publication Title

Journal of Applied Mathematics and Stochastic Analysis

Abstract

In nonlinear estimation problems with linear models, one difficulty in obtaining optimal designs is their dependence on the true value of the unknown parameters. A Bayesian approach is adopted with the assumption the means are independent apriori and have conjuguate prior distributions. The problem of designing an exper- iment to estimate the product of the means of two normal populations is considered. The main results determine an asymptotic lower bound for the Bayes risk, and a necessary and sufficient condition for any sequential procedure to achieve the bound.

First Page

15

Last Page

25

DOI

10.1155/S104895339000003X

Publication Date

1990

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