Bayesian Analysis of the Regression Model with Autocorrelated Errors

Abstract In this paper, regression models with error terms generated by a first order autoregressive scheme are analyzed from a Bayesian point of view. Methods are developed for computing posterior distributions of regression coefficients and the parameter of the autoregressive process. The relationship of our approach to sampling theory approaches is briefly discussed.