  We investigate the problem of estimating the product of means of independent
populations from the one parameter exponential family in a Bayesian framework.
We give a random design which allocates mi the number of observations from
population Pi such that the Bayes risk associated with squared error loss and
cost per unit observation is as small as possible. The design is shown to be
asymptotically optimal.
