Selecting the Prior Distribution in Bayesian Estimation

A major problem associated with Bayesian estimation is selecting the prior distribution. Fisher´s information measure is extended to cover prior distributions so that a comparative measure of the amount of information in the sample and in the prior is obtained. The amount of information is used as an intuitive measure of the relative value or weight of experimental data and prior information. By determining the relative weights of both types of information beforehand, it is possible to select a prior which has a known and controlled influence on the estimation process.