simulate.kppm {spatstat} | R Documentation |
Generates simulated realisations from a fitted cluster point process model.
## S3 method for class 'kppm': simulate(object, nsim = 1, seed=NULL, ..., window=NULL, covariates=NULL)
object |
Fitted cluster point process model. An object of class "kppm" .
|
nsim |
Number of simulated realisations. |
seed |
an object specifying whether and how to initialise
the random number generator. Either NULL or an integer that will
be used in a call to set.seed
before simulating the point patterns.
|
... |
Ignored. |
window |
Optional. Window (object of class "owin" ) in which the
model should be simulated.
|
covariates |
Optional. A named list containing new values for the covariates in the model. |
This function is a method for the generic function
simulate
for the class "kppm"
of fitted
cluster point process models.
Simulations are performed by rThomas
or rMatClust
depending on the cluster mechanism.
The return value is a list of point patterns.
It also carries an attribute "seed"
that
captures the initial state of the random number generator.
This follows the convention used in
simulate.lm
(see simulate
).
It can be used to force a sequence of simulations to be
repeated exactly, as shown in the examples for simulate
.
A list of length nsim
containing simulated point patterns
(objects of class "ppp"
).
The return value also carries an attribute "seed"
that
captures the initial state of the random number generator.
See Details.
Adrian Baddeley adrian@maths.uwa.edu.au http://www.maths.uwa.edu.au/~adrian/ and Rolf Turner r.turner@auckland.ac.nz
data(redwood) fit <- kppm(redwood, ~1, "Thomas") simulate(fit, 2)