simulate.ppm

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Simulate a Fitted Gibbs Point Process Model

Generates simulated realisations from a fitted Gibbs or Poisson point process model.

Keywords
models, spatial
Usage
## S3 method for class 'ppm':
simulate(object, nsim=1, ...,
                         start = NULL,
                         control = default.rmhcontrol(object),
                         project=TRUE,
                         verbose=FALSE, progress=(nsim > 1))
Arguments
object
Fitted point process model. An object of class "ppm".
nsim
Number of simulated realisations.
start
Data determining the initial state of the Metropolis-Hastings algorithm. See rmhstart for description of these arguments. Defaults to list(x.start=data.ppm(model))
control
Data controlling the running of the Metropolis-Hastings algorithm. See rmhcontrol for description of these arguments.
...
Ignored.
verbose
Logical flag indicating whether to print progress reports from rmh.ppm during the simulation of each point pattern.
progress
Logical flag indicating whether to print progress reports for the sequence of simulations.
project
Logical flag indicating what to do if the fitted model is invalid (in the sense that the values of the fitted coefficients do not specify a valid point process). If project=TRUE the closest valid model will be simulated; if
Details

This function is a method for the generic function simulate for the class "ppm" of fitted point process models. Simulations are performed by rmh.ppm.

Value

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

See Also

ppm, simulate.kppm, simulate

Aliases
  • simulate.ppm
Examples
data(japanesepines)
  fit <- ppm(japanesepines, ~1, Strauss(0.1))
  simulate(fit, 2)
Documentation reproduced from package spatstat, version 1.24-1, License: GPL (>= 2)

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