Simulate a Fitted Point Process Model on a Linear Network
Generates simulated realisations from a fitted Poisson point process model on a linear network.
## S3 method for class 'lppm'
simulate(object, nsim=1, ...,
new.coef=NULL,
progress=(nsim > 1),
drop=FALSE)object |
Fitted point process model on a linear network.
An object of class |
nsim |
Number of simulated realisations. |
progress |
Logical flag indicating whether to print progress reports for the sequence of simulations. |
new.coef |
New values for the canonical parameters of the model.
A numeric vector of the same length as |
... |
Arguments passed to |
drop |
Logical. If |
This function is a method for the generic function
simulate for the class "lppm" of fitted
point process models on a linear network.
Only Poisson process models are supported so far.
Simulations are performed by rpoislpp.
A list of length nsim containing simulated point patterns
(objects of class "lpp") on the same linear network as the
original data used to fit the model.
The result also belongs to the class "solist", so that it can be
plotted, and the class "timed", so that the total computation
time is recorded.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
, Rolf Turner r.turner@auckland.ac.nz
and Ege Rubak rubak@math.aau.dk
fit <- lppm(unmark(chicago) ~ y) simulate(fit)[[1]]
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