  Statistical modeling plays a fundamental role in understanding the underlying
mechanism of massive data (statistical inference) and predicting the future
(statistical prediction). Although all models are wrong, researchers try their
best to make some of them be useful. The question here is how can we measure
the usefulness of a statistical model for the data in hand? This is key to
statistical prediction. The important statistical problem of testing whether
the observations follow the proposed statistical model has only attracted
relatively few attentions. In this paper, we proposed a new framework for this
problem through building its connection with two-sample distribution
comparison. The proposed method can be applied to evaluate a wide range of
models. Examples are given to show the performance of the proposed method.
