Plot a Signed or Vector-Valued Measure
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.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.
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")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.