spatstat (version 1.4-6)

plot.ppm: plot a Fitted Point Process Model

Description

Given a fitted point process model obtained by mpl, plot the spatial trend and conditional intensity of the model.

Usage

plot.ppm(x, ngrid = c(40,40), superimpose = TRUE, 
                  trend = TRUE, cif = TRUE, pause = TRUE,
                  how=c("persp","image", "contour"), ...)

Arguments

x

A fitted point process model, typically obtained from the maximum pseudolikelihood algorithm mpl. An object of class "ppm".

ngrid

the spatial trend and conditional intensity are to be evaluated and displayed on a rectangular grid (ngrid[1] by ngrid[2] or ngrid by ngrid) of points.

superimpose

logical flag; if TRUE, the original data point pattern will be superimposed on the plots.

trend

logical flag; if TRUE, the spatial trend will be plotted.

cif

logical flag; if TRUE, the conditional intensity will be plotted.

pause

logical flag indicating whether to pause with a prompt after each plot. Set pause=FALSE if plotting to a file.

how

character string or character vector indicating the style or styles of plots to be performed.

...

extra arguments to the plotting functions persp, image and contour.

Value

• none.

Warnings

See warnings in predict.ppm.

Details

This is the plot method for the class "ppm" (see ppm.object for details of this class). It invokes predict.ppm to compute the spatial trend and conditional intensity of the fitted point process model. See predict.ppm for more explanation about spatial trend and conditional intensity. The spatial trend and/or the conditional intensity of the fitted spatial point process model x are computed at the points of a rectangular grid, and these values are plotted successively using persp, image and contour (or only a selection of these three, if how is given). Extra graphical parameters controlling the display may be passed directly via the arguments ... or indirectly reset using spatstat.options.

The default action is to create a rectangular 40 by 40 grid of points in the observation window of the data point pattern, and evaluate the spatial trend and conditional intensity at these locations. If the fitted model had no spatial trend, then the default is to omit plotting this (flat) surface, unless trend=TRUE is set explicitly. If the fitted model was Poisson, so that there were no spatial interactions, then the conditional intensity and spatial trend are identical, and the default is to omit the conditional intensity, unless cif=TRUE is set explicitly.

If the fitted model was a marked point process, then predictions are made and plotted for each possible mark value in turn.

See Also

mpl, ppm.object, predict.ppm, print.ppm, persp, image, contour, plot, spatstat.options

Examples

library(spatstat)
 data(cells)
 Q <- quadscheme(cells)
 m <- mpl(Q, ~1, Strauss(0.05))
 plot(m)

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