Extract Dummy Points Used to Fit a Point Process Model
Given a fitted point process model, this function extracts the `dummy points' of the quadrature scheme used to fit the model.
- fitted point process model (an object of class
An object of class
"ppm" represents a point process model
that has been fitted to data. It is typically produced by
the maximum pseudolikelihood fitting algorithm
mpl algorithm approximates the pseudolikelihood
integral by a sum over a finite set of quadrature points,
which is constructed by augmenting
the original data point pattern by a set of ``dummy'' points.
The fitted model object returned by
contains complete information about this quadrature scheme.
ppm.object for further
This function extracts the dummy points of the quadrature scheme.
A typical use of this function would be to count the number of dummy
points, to gauge the accuracy of the approximation to the
ppm.object for a list of all operations that can be
performed on objects of class
- A point pattern (object of class
require(spatstat) data(cells) fit <- mpl(cells, ~1, Strauss(r=0.1), rbord=0.1) X <- dummy.ppm(fit) X$n # this is the number of dummy points in the quadrature scheme