doi:http://dx.doi.org/10.5705/ss.2010.245
Abstract: In this paper we introduce a generalization of the Neyman-Scott process [#!neyman58!#] that allows for regularity in the parent process. In particular, we consider the special case where the parent process is a Strauss process with offspring points dispersed about the parent points. Such a generalization allows for point realizations that show a mix of regularity and clustering in the points. We work out a closed form approximation of the function for this model and use this to fit the model to data. The approach is illustrated by applications to the locations of a species of trees in a rainforest dataset.
Key words and phrases: Gibbs process, Neyman-Scott process, K-function, regular point process.