spatstat.model (version 3.6-1)

as.tess.rppm: Convert Recursively Partitioned Point Process Model to a Tessellation

Description

Given a recursively partitioned point process model, create a spatial tessellation representing the partition.

Usage

# S3 method for rppm
as.tess(X)

Value

A tessellation (object of class "tess") with numeric marks.

Arguments

X

A recursively partitioned point process model (object of class "rppm" created by rppm).

Author

Adrian Baddeley .

Details

The function as.tess is generic. The function as.tess.rppm is the method for class "rppm".

In a recursively partitioned point process model, the intensity function of the point process can be evaluated at any spatial location by following a decision tree. Each fork in the tree is defined by a split on the value of one of the spatial covariates. The tree is followed until reaching a leaf (terminal node) and this determines the value of the intensity. The tree itself can be visualised by plot.rppm.

This function as.tess.rppm produces a spatial representation of the model. It interprets each fork in the tree as a division of space into two complementary subsets. Each leaf (terminal node) is an intersection of several such sets. The model corresponds to a division of space into disjoint subsets, that is, a tessellation.

The result is a tessellation in which each tile corresponds to a leaf of the decision tree. The tilenames of the tessellation are expressions representing the logical conditions which define each tile (redundant conditions are omitted). The marks of the tessellation are the intensity values.

See Also

rppm

Examples

  fit <- rppm(nztrees ~ x + y)
  V <- as.tess(fit)
  plot(V, do.col=TRUE)
  tilenames(V)
  marks(V)