spatstat (version 1.60-1)

plot.rppm: Plot a Recursively Partitioned Point Process Model

Description

Given a model which has been fitted to point pattern data by recursive partitioning, plot the partition tree or the fitted intensity.

Usage

# S3 method for rppm
plot(x, …, what = c("tree", "spatial"), treeplot=NULL)

Arguments

x

Fitted point process model of class "rppm" produced by the function rppm.

what

Character string (partially matched) specifying whether to plot the partition tree or the fitted intensity.

…

Arguments passed to plot.rpart and text.rpart (if what="tree") or passed to plot.im (if what="spatial") controlling the appearance of the plot.

treeplot

Optional. A function to be used to plot and label the partition tree, replacing the two functions plot.rpart and text.rpart.

Value

If what="tree", a list containing x and y coordinates of the plotted nodes of the tree. If what="spatial", the return value of plot.im.

Details

If what="tree" (the default), the partition tree will be plotted using plot.rpart, and labelled using text.rpart.

If the argument treeplot is given, then plotting and labelling will be performed by treeplot instead. A good choice is the function prp in package rpart.plot.

If what="spatial", the predicted intensity will be computed using predict.rppm, and this intensity will be plotted as an image using plot.im.

See Also

rppm

Examples

# NOT RUN {
    # Murchison gold data
    mur <- solapply(murchison, rescale, s=1000, unitname="km")
    mur$dfault <- distfun(mur$faults)
    # 
    fit <- rppm(gold ~ dfault + greenstone, data=mur)
    #
    opa <- par(mfrow=c(1,2))
    plot(fit)
    plot(fit, what="spatial")
    par(opa)
# }