Inference on a Set of Statistical Models

Abstract

The paper outlines some aspects related to statistical model selection, focusing in particular on inference conducted in the presence of a finite set of parametric models. The point the paper emphasizes is that the basic approaches such as testing, point estimation and confidence region estimation based on a single model are extensible under pertinent modification to inference on a set of models. They are, however, replaced by plural-model testing, `point' model estimation and confidence-set construction of models.