spatstat (version 1.31-3)

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, ...,
                         singlerun = FALSE,
                         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.

singlerun

Logical. Whether to generate the simulated realisations from a single long run of the Metropolis-Hastings algorithm (singlerun=TRUE) or from separate, independent runs of the algorithm (singlerun=FALSE, the default).

start

Data determining the initial state of the Metropolis-Hastings algorithm. See rmhstart for description of these arguments. Defaults to list(n.start=npoints(data.ppm(model))) me

control

Data controlling the running of the Metropolis-Hastings algorithm. See rmhcontrol for description of these arguments.

...

Further arguments passed to rmhcontrol, or to rmh.default, or to covariate functions in the model.

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

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.

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.

If singlerun=FALSE (the default), the simulated patterns are the results of independent runs of the Metropolis-Hastings algorithm. If singlerun=TRUE, a single long run of the algorithm is performed, and the state of the simulation is saved every nsave iterations to yield the simulated patterns.

In the case of a single run, the behaviour is controlled by the parameters nsave,nburn,nrep. These are described in rmhcontrol. They may be passed in the ... arguments or included in control. It is sufficient to specify two of the three parameters nsave,nburn,nrep.

See Also

ppm, simulate.kppm, simulate

Examples

<testonly>op <- spatstat.options(rmh.nrep=10)</testonly>
  fit <- ppm(japanesepines, ~1, Strauss(0.1))
  simulate(fit, 2)
  simulate(fit, 2, singlerun=TRUE, nsave=1e4, nburn=1e4)
  <testonly>spatstat.options(op)</testonly>