spatstat.core (version 2.3-1)

methods.zclustermodel: Methods for Cluster Models

Description

Methods for the experimental class of cluster models.

Usage

# S3 method for zclustermodel
pcfmodel(model, …)
 # S3 method for zclustermodel
Kmodel(model, …)
 # S3 method for zclustermodel
intensity(X, …)
 # S3 method for zclustermodel
predict(object, …,
                  locations, type = "intensity", ngrid = NULL)
 # S3 method for zclustermodel
print(x, …)
 # S3 method for zclustermodel
clusterradius(model,…,thresh=NULL, precision=FALSE)
 # S3 method for zclustermodel
reach(x, …, epsilon)

Arguments

model,object,x,X

Object of class "zclustermodel".

…

Arguments passed to other methods.

locations

Locations where prediction should be performed. A window or a point pattern.

type

Currently must equal "intensity".

ngrid

Pixel grid dimensions for prediction, if locations is a rectangle or polygon.

thresh,epsilon

Tolerance thresholds

precision

Logical value stipulating whether the precision should also be returned.

Value

Same as for other methods.

Details

Experimental.

See Also

zclustermodel

Examples

# NOT RUN {
  m <- zclustermodel("Thomas", kappa=10, mu=5, scale=0.1)
  m2 <- zclustermodel("VarGamma", kappa=10, mu=10, scale=0.1, nu=0.7)
  m
  m2
  g <- pcfmodel(m)
  g(0.2)
  g2 <- pcfmodel(m2)
  g2(1)
  Z <- predict(m, locations=square(2))
  Z2 <- predict(m2, locations=square(1))
  varcount(m, square(1))
  varcount(m2, square(1))
# }