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)
- Intensity of the Poisson process of cluster centres. A single positive number, a function, or a pixel image.
- Diameter of each cluster that consists of exactly 2 points.
- Probability that a cluster contains exactly 2 points.
- Window in which to simulate the pattern.
An object of class
"owin"or something acceptable to
- Number of simulated realisations to be generated.
- Logical. If
drop=TRUE(the default), the result will be a point pattern, rather than a list containing a point pattern.
This algorithm generates a realisation of the Gauss-Poisson
point process inside the window
The process is constructed by first
generating a Poisson point process of parent points
kappa. Then each parent point is either retained
1 - p2)
or replaced by a pair of points at a fixed distance
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
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
pp <- rGaussPoisson(30, 0.07, 0.5)