Plot a fitted cluster point process
Plots a fitted cluster point process model, displaying the fitted intensity and the fitted K-function.
## S3 method for class 'kppm'
plot(x, ...,
what=c("intensity", "statistic", "cluster"),
pause=interactive(),
xname)x |
Fitted cluster point process model.
An object of class |
... |
Arguments passed to |
what |
Character vector determining what will be plotted. |
pause |
Logical value specifying whether to pause between plots. |
xname |
Optional. Character string. The name of the object |
This is a method for the generic function
plot for the class "kppm" of fitted
cluster point process models.
The argument x should be a cluster point process model
(object of class "kppm") obtained using
the function kppm.
The choice of plots (and the order in which they are
displayed) is controlled by the argument what.
The options (partially matched) are "intensity",
"statistic" and "cluster".
This command is capable of producing three different plots:
specifies the fitted intensity of the model,
which is plotted using plot.ppm. By default this plot
is not produced for stationary models.
specifies the empirical and fitted summary
statistics, which are plotted using plot.fv. This is
only meaningful if the model has been fitted using the Method of
Minimum Contrast, and it is turned off otherwise.
specifies a fitted cluster, which is computed
by clusterfield and plotted by
plot.im. It is only meaningful for Poisson cluster
(incl. Neyman-Scott) processes, and it is turned off for
log-Gaussian Cox processes (LGCP). If the model is stationary (and
non-LGCP) this option is turned on by default and shows a fitted
cluster positioned at the centroid of the observation window. For
non-stationary (and non-LGCP) models this option is only invoked if
explicitly told so, and in that case an additional argument
locations (see clusterfield) must be given to
specify where to position the parent point(s) .
Alternatively what="all" selects all available options.
Null.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
Rolf Turner r.turner@auckland.ac.nz
and Ege Rubak rubak@math.aau.dk
data(redwood) fit <- kppm(redwood~1, "Thomas") plot(fit)
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