  We propose the use of the probability integral transform (PIT) for model
validation in point process models. The simple PIT diagnostics assess the
calibration of the model and can detect inconsistencies in both the intensity
and the interaction structure. For the Poisson model, the PIT diagnostics can
be calculated explicitly. Generally, the calibration may be assessed
empirically based on random draws from the model and the method applies to
processes of any dimension.
