The argument x represents a fitted spatial point process model
or a similar object. is.stationary(x) returns TRUE if x represents
a stationary point process, and FALSE if not.
is.poisson(x) returns TRUE if x represents
a Poisson point process, and FALSE if not.
The functions is.stationary and is.poisson are generic,
with methods for the classes "ppm" (Gibbs point process models),
"kppm" (cluster or Cox point process models),
"slrm" (spatial logistic regression models) and
"rmhmodel" (model specifications for the
Metropolis-Hastings algorithm).
Additionally is.poisson has a method for
class "interact" (interaction structures for Gibbs models).
is.poisson.kppm will return FALSE, unless
the model x is degenerate:
either x has zero intensity so that its realisations are empty
with probability 1, or it is a log-Gaussian Cox process
where the log intensity has zero variance.
is.poisson.slrm will always return TRUE,
by convention.