simulate.kppm

0th

Percentile

Simulate a Fitted Cluster Point Process Model

Generates simulated realisations from a fitted cluster point process model.

Keywords
models, spatial
Usage
## S3 method for class 'kppm':
simulate(object, nsim = 1, seed=NULL, ...,
         window=NULL, covariates=NULL, verbose=TRUE)
Arguments
object
Fitted cluster point process model. An object of class "kppm".
nsim
Number of simulated realisations.
seed
an object specifying whether and how to initialise the random number generator. Either NULL or an integer that will be used in a call to set.seed before simulating the p
...
Ignored.
window
Optional. Window (object of class "owin") in which the model should be simulated.
covariates
Optional. A named list containing new values for the covariates in the model.
verbose
Logical. Whether to print progress reports (when nsim > 1).
Details

This function is a method for the generic function simulate for the class "kppm" of fitted cluster point process models. Simulations are performed by rThomas, rMatClust or rLGCP depending on the model.

The return value is a list of point patterns. It also carries an attribute "seed" that captures the initial state of the random number generator. This follows the convention used in simulate.lm (see simulate). It can be used to force a sequence of simulations to be repeated exactly, as shown in the examples for simulate.

Value

  • A list of length nsim containing simulated point patterns (objects of class "ppp").

    The return value also carries an attribute "seed" that captures the initial state of the random number generator. See Details.

See Also

kppm, rThomas, rMatClust, rLGCP, simulate.ppm, simulate

Aliases
  • simulate.kppm
Examples
data(redwood)
  fit <- kppm(redwood, ~1, "Thomas")
  simulate(fit, 2)
Documentation reproduced from package spatstat, version 1.31-3, License: GPL (>= 2)

Community examples

Looks like there are no examples yet.