plot.plotppm | R Documentation |
The function plot.ppm produces objects which specify plots of fitted point process models. The function plot.plotppm carries out the actual plotting of these objects.
## S3 method for class 'plotppm'
plot(x, data = NULL, trend = TRUE, cif = TRUE,
se = TRUE, pause = interactive(),
how = c("persp", "image", "contour"),
..., pppargs)
x |
An object of class |
.
data |
The point pattern (an object of class |
trend |
Logical scalar; should the trend component of the fitted model be plotted? |
cif |
Logical scalar; should the complete conditional intensity of the fitted model be plotted? |
se |
Logical scalar; should the estimated standard error of the fitted intensity be plotted? |
pause |
Logical scalar indicating whether to pause with a prompt
after each plot. Set |
how |
Character string or character vector indicating the style or styles of plots to be performed. |
... |
Extra arguments to the plotting functions
|
pppargs |
List of extra arguments passed to |
If argument data
is supplied then the point pattern will
be superimposed on the image and contour plots.
Sometimes a fitted model does not have a trend component, or the
trend component may constitute all of the conditional intensity (if
the model is Poisson). In such cases the object x
will not
contain a trend component, or will contain only a trend component.
This will also be the case if one of the arguments trend
and cif
was set equal to FALSE
in the call to
plot.ppm()
which produced x
. If this is so then
only the item which is present will be plotted. Explicitly setting
trend=TRUE
, or cif=TRUE
, respectively, will then give
an error.
None.
Arguments which are passed to persp
, image
, and
contour
via the ... argument get passed to any of the
other functions listed in the how
argument, and won't be
recognized by them. This leads to a lot of annoying but harmless
warning messages. Arguments to persp
may be supplied via
spatstat.options()
which alleviates the warning
messages in this instance.
and \rolf
plot.ppm()
if(interactive()) {
m <- ppm(cells ~ 1, Strauss(0.05))
mpic <- plot(m)
# Perspective plot only, with altered parameters:
plot(mpic,how="persp", theta=-30,phi=40,d=4)
# All plots, with altered parameters for perspective plot:
op <- spatstat.options(par.persp=list(theta=-30,phi=40,d=4))
plot(mpic)
# Revert
spatstat.options(op)
}
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