Statistica Sinica 9(1999), 893-904
A ROBUST ASYMPTOTICALLY OPTIMAL PROCEDURE IN
BAYES SEQUENTIAL ESTIMATION
Leng-Cheng Hwang
Tamkang University
Abstract:
The problem of sequential estimation of the mean, subject to the loss
defined as the sum of squared error loss and sampling costs, is considered
within the
Bayesian framework. It is shown that the sequential procedure, as proposed by
Chow and Yu (1981) in classical non-Bayesian sequential estimation, is,
in fact, asymptotically Bayes for a large class
of prior distributions. The proposed procedure, without using any auxiliary
data, is robust in the sense that it does not depend on the distribution of
outcome variables and the prior.
Key
words and phrases:
Asymptotically Bayes, Bayes sequential estimation, Bayes risk, optimal
sequential procedure, prior distributions.