PREDICTIVE SPECIFICATION OF PRIOR MODEL PROBABILITIES IN VARIABLE SELECTION

We examine the problem of specifying prior probabilities for all possi ble subset models in the context of variable selection in normal linea r models. A solution is proposed that uses a prior prediction for the observable, an associated weight, and prior opinion regarding error pr ecision as the only required input. Numerical examples are given to il lustrate the method.