Nonparametric goodness-of-fit

This paper develops an approach to testing the adequacy of both classical:and Bayesian models given sample data. An important. feature of the approach is that we are able to test the practical scientific hypothesis of whether the true underlying model is-close to some hypothesized model. The notion of closeness is based on measurement precision anti requires the introduction of a metric for which we consider the Kolmogorov distance. The approach is nonparametric in the sense that the model under the alternative hypothesis is a:Dirichlet process.