"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)
"ppm"
.
singlerun=TRUE
) or from separate, independent runs of the
algorithm (singlerun=FALSE
, the default).
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.
rmhcontrol
for description of these arguments.
"owin"
.
rmhcontrol
,
or to rmh.default
, or to covariate functions in the model.
project=TRUE
the closest valid model will be simulated;
if project=FALSE
an error will occur.
rmh.ppm
during the simulation of each point pattern.
coef(object)
.
nsim=1
and drop=TRUE
, the
result will be a point pattern, rather than a list
containing a point pattern.
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.
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
.
ppm
,
simulate.kppm
,
simulate
fit <- ppm(japanesepines, ~1, Strauss(0.1))
simulate(fit, 2)
simulate(fit, 2, singlerun=TRUE, nsave=1e4, nburn=1e4)
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