is.multitype.ppm {spatstat.model} | R Documentation |
Test Whether A Point Process Model is Multitype
Description
Tests whether a fitted point process model involves “marks” attached to the points that classify the points into several types.
Usage
## S3 method for class 'ppm'
is.multitype(X, ...)
Arguments
X |
Fitted point process model (object of class |
... |
Ignored. |
Details
“Marks” are observations attached to each point of a point pattern.
For example the longleaf
dataset
contains the locations of trees, each tree being marked by its diameter;
the amacrine
dataset gives the locations of cells
of two types (on/off) and the type of cell may be regarded as a mark attached
to the location of the cell.
The argument X
is a fitted point process model
(an object of class "ppm"
) typically obtained
by fitting a model to point pattern data using ppm
.
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). Currently we have not implemented a test for 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.
Value
Logical value, equal to TRUE
if
X
is a model that was fitted to a multitype point pattern dataset.
Author(s)
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
and Rolf Turner rolfturner@posteo.net
See Also
is.multitype
,
is.multitype.ppp
Examples
X <- lansing
# Multitype point pattern --- trees marked by species
fit1 <- ppm(X, ~ marks, Poisson())
is.multitype(fit1)
# TRUE
fit2 <- ppm(X, ~ 1, Poisson())
is.multitype(fit2)
# TRUE
# Unmarked point pattern
fit3 <- ppm(cells, ~ 1, Poisson())
is.multitype(fit3)
# FALSE