| Abstract: | The author proposes a general method for evaluating the fit of a model for functional data. His approach consists of embedding the proposed model into a larger family of models, assuming the true process generating the data is within the larger family, and then computing a posterior distribution for the Kullback‐Leibler distance between the true and the proposed models. The technique is illustrated on biomechanical data reported by Ramsay, Flanagan & Wang (1995). It is developed in detail for hierarchical polynomial models such as those found in Lindley & Smith (1972), and is also generally applicable to longitudinal data analysis where polynomials are fit to many individuals. |
