# plot.rppm

##### Plot a Recursively Partitioned Point Process Model

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`

.

##### 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`

.

##### 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`

.

##### See Also

##### 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)
# }
```

*Documentation reproduced from package spatstat, version 1.59-0, License: GPL (>= 2)*