A class ppm to represent a fitted stochastic model
for a point process. The output of mpl.
Arguments
Warnings
The internal representation may change in the next few releases
of the spatstat package.
Details
An object of class ppm represents a stochastic point process
model that has been fitted to a point pattern dataset.
Typically it is the output of the maximum pseudolikelihood model fitter,
mpl. There are methods print.ppm,
predict.ppm and plot.ppm
A ppm object contains at least the following entries:
ll{
coef the fitted regular parameters (as returned by
glm)
trend the trend formula or NULLinteraction the point process interaction family
(an object of class "interact")
or NULLQ the quadrature scheme used
maxlogpl the maximised value of log pseudolikelihood
correction name of edge correction method used
}
See mpl for explanation of these concepts.
The irregular parameters (e.g. the interaction radius of the
Strauss process) are encoded in the interaction entry.
See also (for example) Strauss
to understand how to specify
a point process model with unknown parameters.
library(spatstat)
data(cells)
fit <- mpl(cells, ~ x, Strauss(0.1), correction="periodic")
fit
pred <- predict(fit)
pred <- predict(fit, nx=50, ny=50, type="trend")
plot(fit)