Bayesian inference for a random tessellation process.
This article describes an inhomogeneous Poisson point process in the plane with an intensity function based on a Dirichlet tessellation process and a method for using observations on the point process to make fully Bayesian inferences about the underlying tessellation. The method is implemented using a Markov chain Monte Carlo approach. An application to modeling the territories of clans of badgers, Meles meles, is described.
Blackwell
P G
PG
Department of Probability and Statistics, University of Sheffield, UK. P.Blackwell@sheffield.ac.uk
D000818:Animals; D001499:Bayes Theorem; D002335:Carnivora; D003710:Demography; D004739:England; D015233:Models, Statistical; D011897:Random Allocation; D013731:Territoriality