Generates simulated realisations from a fitted spatial logistic regresson model
# S3 method for slrm
simulate(object, nsim = 1, seed=NULL, ...,
window=NULL, covariates=NULL, verbose=TRUE, drop=FALSE)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.
Fitted spatial logistic regression model. An object of class "slrm".
Number of simulated realisations.
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.
Optional. Window (object of class "owin") in which the
model should be simulated.
Optional. A named list containing new values for the covariates in the model.
Logical. Whether to print progress reports (when nsim > 1).
Logical. If nsim=1 and drop=TRUE, the
result will be a point pattern, rather than a list
containing a point pattern.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au and Rolf Turner rolfturner@posteo.net
This function is a method for the generic function
simulate for the class "slrm" of fitted
spatial logistic regression models.
Simulations are performed by rpoispp
after the intensity has been computed by predict.slrm.
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.
slrm,
rpoispp,
simulate.ppm,
simulate.kppm,
simulate
X <- copper$SouthPoints
fit <- slrm(X ~ 1)
simulate(fit, 2)
fitxy <- slrm(X ~ x+y)
simulate(fitxy, 2, window=square(2))
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