simulate.sphppm: Simulate Realisations of a Fitted Point Process Model on...

In baddstats/spherstat: Spatial Point Pattern Analysis, Geometry and Trigonometry for the Sphere

Simulate Realisations of a Fitted Point Process Model on Sphere

Description

Given a point process model fitted to spherical point pattern data, this function generates one or more simulated realisations of the model.

Usage

## S3 method for class 'sphppm'
simulate(object, nsim = 1, ..., win, drop = TRUE)

Arguments

object	The fitted model. An object of class "sphppm" usually obtained from sphppm.
win	The window in which to generate the simulated realisations. An object of class "sphwin". Default is the window for the data to which the model was originally fitted.
nsim	Number of simulations. Integer.
...	Ignored.
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 is the method for the generic function simulate for the class "sphppm" of fitted point process models on a sphere.

Simulated realisations of the model are generated using rpoispp.sphwin, using predict.sphppm to evaluate the intensity function.

Value

If nsim=1 and drop=TRUE (the defaults), a spherical point pattern (object of class "sp2"). Otherwise, a list of point patterns.

Author(s)

Adrian Baddeley.

See Also

sphppm, rpoispp.sphwin

Examples

   W <- sphwin(type="band", param=c(pi/3, 2*pi/3), ref=c(0,0))
   Z <- runif.sphwin(100, W)
   fut <- sphppm(Z ~ x1 + x2 + x3)
   simulate(fut, 2)

baddstats/spherstat documentation built on Feb. 6, 2023, 1:45 a.m.