# prune.rppm

From spatstat v1.60-1
by Adrian Baddeley

##### Prune a Recursively Partitioned Point Process Model

Given a model which has been fitted to point pattern data by recursive partitioning, apply pruning to reduce the complexity of the partition tree.

##### Usage

```
# S3 method for rppm
prune(tree, …)
```

##### Arguments

- tree
Fitted point process model of class

`"rppm"`

produced by the function`rppm`

.- …
Arguments passed to

`prune.rpart`

to control the pruning procedure.

##### Details

This is a method for the generic function `prune`

for the class `"rppm"`

. An object of this class is a
point process model, fitted to point pattern data by
recursive partitioning, by the function `rppm`

.

The recursive partition tree will be pruned using
`prune.rpart`

. The result is another
object of class `"rppm"`

.

##### Value

Object of class `"rppm"`

.

##### 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)
fit
prune(fit, cp=0.1)
# }
```

*Documentation reproduced from package spatstat, version 1.60-1, License: GPL (>= 2)*

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