simulate.ppm
Simulate a Fitted Gibbs Point Process Model
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 tolist(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 tormh.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.
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"
).
See Also
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>