spatstat.core (version 2.3-1)

dummy.ppm: Extract Dummy Points Used to Fit a Point Process Model

Description

Given a fitted point process model, this function extracts the `dummy points' of the quadrature scheme used to fit the model.

Usage

dummy.ppm(object, drop=FALSE)

Arguments

object

fitted point process model (an object of class "ppm").

drop

Logical value determining whether to delete dummy points that were not used to fit the model.

Value

A point pattern (object of class "ppp").

Details

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".

See Also

ppm.object, ppp.object, ppm

Examples

# NOT RUN {
 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
# }