Bayesian analysis of regression problems

Abstract

SUMMARY A general Bayesian formulation of the regression problem is considered, which derives from a direct specification of a prior distribution for the unknown joint probability distribution of the random variables. The resulting estimators are related to the least squares and ridge estimators of the regression coefficients.