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.
dummy.ppm(object, drop=FALSE)
object |
fitted point process model (an object of class |
drop |
Logical value determining whether to delete dummy points that were not used to fit the model. |
An object of class "ppm" represents a point process model
that has been fitted to data. It is typically produced by
the model-fitting algorithm ppm.
The maximum pseudolikelihood algorithm in ppm
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 ppm
contains complete information about this quadrature scheme.
See ppm or ppm.object for further
information.
This function dummy.ppm
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
exact pseudolikelihood.
It may happen that some dummy points are not actually used in
fitting the model (typically because the value of a covariate is NA
at these points). The argument drop specifies whether these
unused dummy points shall be deleted (drop=TRUE) or
retained (drop=FALSE) in the return value.
See ppm.object for a list of all operations that can be
performed on objects of class "ppm".
A point pattern (object of class "ppp").
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
and Rolf Turner r.turner@auckland.ac.nz
data(cells) fit <- ppm(cells, ~1, Strauss(r=0.1)) X <- dummy.ppm(fit) npoints(X) # this is the number of dummy points in the quadrature scheme
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