  $P$-values have been the focus of considerable criticism based on various
considerations. Still, the $P$-value represents one of the most commonly used
statistical tools. When assessing the suitability of a single hypothesized
distribution, it is not clear that there is a better choice for a measure of
surprise. This paper is concerned with the definition of appropriate
model-based $P$-values for model checking.
