simulate.ppm {spatstat} | R Documentation |
Generates simulated realisations from a fitted Gibbs or Poisson point process model.
## S3 method for class 'ppm': simulate(object, nsim=1, ..., start = NULL, control = rmhcontrol(), project=TRUE, verbose=FALSE, progress=TRUE)
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 project=FALSE an error will occur.
|
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
.
A list of length nsim
containing simulated point patterns
(objects of class "ppp"
).
Adrian Baddeley adrian@maths.uwa.edu.au http://www.maths.uwa.edu.au/~adrian/ and Rolf Turner r.turner@auckland.ac.nz
data(japanesepines) fit <- ppm(japanesepines, ~1, Strauss(0.1)) simulate(fit, 2)