Test Whether A Point Process Model is Multitype
Tests whether a fitted point process model on a network involves “marks” attached to the points that classify the points into several types.
## S3 method for class 'lppm' is.multitype(X, ...)
X |
Fitted point process model on a linear network
(object of class |
... |
Ignored. |
“Marks” are observations attached to each point of a point pattern.
For example the chicago dataset contains
the locations of crimes, each crime location
being marked by the type of crime.
The argument X is a fitted point process model
on a network (an object of class "lppm") typically obtained
by fitting a model to point pattern data on a network
using lppm.
This function returns TRUE if the original data
(to which the model X was fitted) were a multitype point pattern.
Note that this is not the same as testing whether the model involves terms that depend on the marks (i.e. whether the fitted model ignores the marks in the data). See the Examples for a trick for doing this.
If this function returns TRUE, the implications are
(for example) that
any simulation of this model will require simulation of random marks
as well as random point locations.
Logical value, equal to TRUE if
X is a model that was fitted to a multitype point pattern dataset.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au and Rolf Turner r.turner@auckland.ac.nz
fit <- lppm(chicago ~ x) is.multitype(fit) # TRUE because chicago data are multitype ## To check whether the model involves marks: "marks" %in% spatstat.utils::variablesinformula(formula(fit))
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