Comment

A nonparametric Bayesian modeling is described and is compared to the one used by Shively, Kohn and Wood in their study. The former is concerned with broad features of the data, such as the general form in which a covariate enters the model or if interaction terms are required. A parametric element is needed when there is a substantive differential effect across a range of values for a covariate. For instance, a piecewise linear term, can account for most of the overall trend of the data.
This is a landmark article in applied statistics. It takes a subject of interest to many, who is the best - in hockey, golf and baseball - and applies a [...]