  It is a relatively well-known fact that in problems of Bayesian model
selection improper priors should, in general, be avoided. In this paper we
derive a proper and parsimonious uniform prior for regression coefficients. We
then use this prior to derive the corresponding evidence values of the
regression models under consideration. By way of these evidence values one may
proceed to compute the posterior probabilities of the competing regression
models.
