R: Simulate a Fitted Gibbs Point Process Model

simulate.ppm {spatstat} | R Documentation

## 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, w=w),
                             w = NULL,
                             project=TRUE, new.coef=NULL,
                             verbose=FALSE, progress=(nsim > 1),
                             drop=FALSE)

### 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(object)))` meaning that the initial state of the algorithm has the same number of points as the original dataset.
`control` | Data controlling the running of the Metropolis-Hastings algorithm. See `rmhcontrol` for description of these arguments.
`w` | Optional. The window in which the model is defined. An object of class `"owin"`.
`...` | 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 `project=FALSE` an error will occur.
`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.
`new.coef` | New values for the canonical parameters of the model. A numeric vector of the same length as `coef(object)`.
`drop` | Logical. If `nsim=1` and `drop=TRUE`, the result will be a point pattern, rather than a list containing a point pattern.

### 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`.

### Value

A list of length `nsim` containing simulated point patterns (objects of class `"ppp"`). It also belongs to the class `"solist"`, so that it can be plotted, and the class `"timed"`, so that the total computation time is recorded.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au

and Rolf Turner r.turner@auckland.ac.nz

### See Also

`ppm`, `simulate.kppm`, `simulate`

### Examples

      fit <- ppm(japanesepines, ~1, Strauss(0.1))
      simulate(fit, 2)
      simulate(fit, 2, singlerun=TRUE, nsave=1e4, nburn=1e4)

[Package spatstat version 1.54-0 Index]