| prune.rppm {spatstat} | R Documentation |
Given a model which has been fitted to point pattern data by recursive partitioning, apply pruning to reduce the complexity of the partition tree.
## S3 method for class 'rppm' prune(tree, ...)
tree |
Fitted point process model of class |
... |
Arguments passed to |
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".
Object of class "rppm".
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk
rppm,
plot.rppm,
predict.rppm.
# 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)