The Smoothness Priors Concept

The “history” of smoothness priors essentially starts with a problem addressed in Whittaker (1923). It was followed by Shiller (1973), and Akaike (1980a) in which the framework initiated by Shiller was continued Akaike (1980a) was a quasi-Bayesian Gaussian disturbances linear regression, least squares computations, model framework. Stochastic difference equation constraints were placed on the prior distributions of the model parameters. The critical computation was that of the likelihood of hyperparameters of those distributions. Our own work and a considerable amount of other work was motivated by Akaike (1980a). Here we identify some of that work and some relationship of that work to other research as well as developments and extensions. The least squares computational framework of smoothness priors is also presented here.