spatstat (version 1.16-2)

simulate.ppm: Simulate a Fitted Gibbs Point Process Model

Description

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

Usage

## S3 method for class 'ppm':
simulate(object, nsim=1, ...,
                         start = NULL,
                         control = rmhcontrol(),
                         project=TRUE,
                         verbose=FALSE, progress=TRUE)

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

Value

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

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.

See Also

ppm, simulate.kppm, simulate

Examples

data(japanesepines)
  fit <- ppm(japanesepines, ~1, Strauss(0.1))
  simulate(fit, 2)