Simulate Thomas Process
Generate a random point pattern using the Thomas cluster process.
rThomas(lambda, sigma, mu, win = owin(c(0,1),c(0,1)))
- Intensity of the Poisson process of cluster centres. A single positive number.
- Standard deviation of displacement of a point from its cluster centre.
- Expected number of points per cluster.
- Window in which to simulate the pattern.
An object of class
"owin"or something acceptable to
This algorithm generates a realisation of the
Thomas process, a special case of the Neyman-Scott process.
generates a uniform Poisson point process of ``parent'' points
lambda. Then each parent point is
replaced by a random cluster of points, the number of points
per cluster being Poisson (
mu) distributed, and their
positions being isotropic Gaussian displacements from the
cluster parent location.
- The simulated point pattern (an object of class
Additionally, some intermediate results of the simulation are returned as attributes of this point pattern. See
X <- rThomas(10, 0.2, 5)