represents a Thomas cluster point process with density μ, cluster mean λ and scale parameter σ in .
- ThomasPointProcess models clustered point configurations with centers uniformly distributed over space and cluster points isotropically distributed with a light-tail radial distribution.
- Typical uses include areas like cosmology, where the clusters are galaxy clusters, or plant ecology.
- The cluster centers are placed according to PoissonPointProcess with density μ.
- The point count of a cluster is distributed according to PoissonDistribution with mean λ.
- The cluster points in each cluster are isotropically distributed with the radial distribution NormalDistribution[0,σ] centered at a cluster center.
- ThomasPointProcess allows μ, λ and σ to be any positive real numbers, and d to be any positive integer.
- The following settings can be used for PointProcessEstimator for estimating ThomasPointProcess:
"FindClusters" use FindClusters function "MethodOfMoments" use a homogeneity measure to estimate the parameters
- ThomasPointProcess can be used with such functions as RipleyK, PointCountDistribution and RandomPointConfiguration.
Examplesopen allclose all
Basic Examples (4)
Properties & Relations (5)
PointCountDistribution is known:
Wolfram Research (2020), ThomasPointProcess, Wolfram Language function, https://reference.wolfram.com/language/ref/ThomasPointProcess.html.
Wolfram Language. 2020. "ThomasPointProcess." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/ThomasPointProcess.html.
Wolfram Language. (2020). ThomasPointProcess. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ThomasPointProcess.html