How Should the Statistical Expert System and its User See Each Other?

Abstract

This paper draws on experience that my colleagues and I have had in constructing GLIMPSE, a knowledge-based front-end for GLIM. GLIM is a statistical package that facilitates the specification, fitting, and checking of the class of generalized linear models (McCullagh and Neider, 1983). It has its own interpretive language, sufficiently powerful to allow the user to program his own non-standard analyses if a model falls outside the built-in set. GLIM gives the user little on-line syntactic help (how to do things), and almost no semantic help (what to do), except to comment on unsuitable models which produce, for example, negative fitted values when these must be positive. Front ends are designed to remedy these deficiencies, by providing help of both kinds. The result, in the case of GLIMPSE, is a system with three-way communication taking place between the user, the front-end and GLIM itself, which serves as the algorithmic engine.