simulate.lppm: Simulate a Fitted Point Process Model on a Linear Network

In spatstat.linnet: Linear Networks Functionality of the 'spatstat' Family

Simulate a Fitted Point Process Model on a Linear Network

Description

Generates simulated realisations from a fitted Poisson point process model on a linear network.

Usage

  ## S3 method for class 'lppm'
simulate(object, nsim=1, ...,
                         new.coef=NULL,
                         progress=(nsim > 1),
                         drop=FALSE)

Arguments

object	Fitted point process model on a linear network. An object of class "lppm".
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 coef(object).
...	Arguments passed to predict.lppm to determine the spatial resolution of the image of the fitted intensity used in the simulation.
drop	Logical. If nsim=1 and drop=TRUE, the result will be a point pattern, rather than a list containing a point pattern.

Details

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.

Value

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.

Author(s)

\adrian

, \rolf

and \ege

See Also

lppm, rpoislpp, simulate

Examples

  fit <- lppm(unmark(chicago) ~ y)
  simulate(fit)[[1]]

spatstat.linnet documentation built on Sept. 20, 2024, 5:06 p.m.