Abstract
We consider the problem of modifying the linear Bayes estimator for the mean of a distribution of unknown form by using an estimate of sample variance. The general conditions under which there is no advantageous variance modification to the linear Bayes rule are identified. These results are applied to the problem of sampling from a normal distribution with unknown mean and variance, and the implications are discussed.

This publication has 0 references indexed in Scilit: