plot.msr | R Documentation |
Plot a signed measure or vector-valued measure.
## S3 method for class 'msr' plot(x, ..., add = FALSE, how = c("image", "contour", "imagecontour"), main = NULL, do.plot = TRUE, multiplot = TRUE, massthresh = 0, equal.markscale = FALSE, equal.ribbon = FALSE)
x |
The signed or vector measure to be plotted.
An object of class |
... |
Extra arguments passed to |
add |
Logical flag; if |
how |
String indicating how to display the continuous density component. |
main |
String. Main title for the plot. |
do.plot |
Logical value determining whether to actually perform the plotting. |
multiplot |
Logical value indicating whether it is permissible to display a plot with multiple panels (representing different components of a vector-valued measure, or different types of points in a multitype measure.) |
massthresh |
Threshold for plotting atoms.
A single numeric value or |
equal.markscale |
Logical value indicating whether different panels should use the same symbol map (to represent the masses of atoms of the measure). |
equal.ribbon |
Logical value indicating whether different panels should use the same colour map (to represent the density values in the diffuse component of the measure). |
This is the plot
method for the class "msr"
.
The continuous density component of x
is interpolated
from the existing data by Smooth.ppp
,
and then displayed as a colour image by plot.im
.
The discrete atomic component of x
is then superimposed on this
image by plotting the atoms as circles (for positive mass)
or squares (for negative mass) by plot.ppp
.
By default, atoms with zero mass are not plotted at all.
To smooth both the discrete and continuous components,
use Smooth.msr
.
Use the argument clipwin
to restrict the plot to a subset
of the full data.
To remove atoms with tiny masses, use the argument massthresh
.
(Invisible) colour map (object of class "colourmap"
) for the
colour image.
.
msr
,
Smooth.ppp
,
Smooth.msr
,
plot.im
,
plot.ppp
X <- rpoispp(function(x,y) { exp(3+3*x) }) fit <- ppm(X, ~x+y) rp <- residuals(fit, type="pearson") rs <- residuals(fit, type="score") plot(rp) plot(rs) plot(rs, how="contour")
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