rThomas {spatstat}R Documentation

Simulate Thomas Process

Description

Generate a random point pattern using the Thomas cluster process.

Usage

 rThomas(lambda, sigma, mu, win = owin(c(0,1),c(0,1)))

Arguments

lambda Intensity of the Poisson process of cluster centres. A single positive number.
sigma Standard deviation of displacement of a point from its cluster centre.
mu Expected number of points per cluster.
win Window in which to simulate the pattern. An object of class "owin" or something acceptable to as.owin.

Details

This algorithm generates a realisation of the Thomas process, a special case of the Neyman-Scott process.

The algorithm generates a uniform Poisson point process of ``parent'' points with intensity 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.

Value

The simulated point pattern (an object of class "ppp").

Author(s)

Adrian Baddeley adrian@maths.uwa.edu.au http://www.maths.uwa.edu.au/~adrian/ and Rolf Turner rolf@math.unb.ca http://www.math.unb.ca/~rolf

See Also

rpoispp, rNeymanScott

Examples

  X <- rThomas(10, 0.2, 5)

[Package spatstat version 1.6-8 Index]