Simulate Gauss-Poisson Process
Generate a random point pattern, a simulated realisation of the Gauss-Poisson Process.
rGaussPoisson(kappa, r, p2, win = owin(c(0,1),c(0,1)),
..., nsim=1, drop=TRUE)kappa |
Intensity of the Poisson process of cluster centres. A single positive number, a function, or a pixel image. |
r |
Diameter of each cluster that consists of exactly 2 points. |
p2 |
Probability that a cluster contains exactly 2 points. |
win |
Window in which to simulate the pattern.
An object of class |
... |
Ignored. |
nsim |
Number of simulated realisations to be generated. |
drop |
Logical. If |
This algorithm generates a realisation of the Gauss-Poisson
point process inside the window win.
The process is constructed by first
generating a Poisson point process of parent points
with intensity kappa. Then each parent point is either retained
(with probability 1 - p2)
or replaced by a pair of points at a fixed distance r apart
(with probability p2). In the case of clusters of 2 points,
the line joining the two points has uniform random orientation.
In this implementation, parent points are not restricted to lie in the window; the parent process is effectively the uniform Poisson process on the infinite plane.
A point pattern (an object of class "ppp")
if nsim=1, or a list of point patterns if nsim > 1.
Additionally, some intermediate results of the simulation are
returned as attributes of the point pattern.
See rNeymanScott.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
and Rolf Turner r.turner@auckland.ac.nz
pp <- rGaussPoisson(30, 0.07, 0.5)
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