# dummy.ppm

0th

Percentile

##### 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.

Keywords
models, utilities, spatial
##### 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.
##### 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".

##### Value

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

ppm.object, ppp.object, ppm

• dummy.ppm
##### Examples
data(cells)
fit <- ppm(cells, ~1, Strauss(r=0.1))
X <- dummy.ppm(fit)
X\$n
# this is the number of dummy points in the quadrature scheme`
Documentation reproduced from package spatstat, version 1.23-2, License: GPL (>= 2)

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