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 `"ppm"`

).

drop

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

A point pattern (object of class `"ppp"`

).

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"`

.

# 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 # }