Inference for Over- and Under-dispersed Point Processes
Robert Wolpert and Katja Ickstadt
Duke University and Technische Universität Darmstadt
August 2000
Some point process models are only appropriate for over-dispersed point
distributions more irregular than Poisson point processes, while many others
are appropriate only for under-dispersed distributions. Markov point
processes may be appropriate for either over- or under-dispersed point
distributions, but the extraordinary difficulty of calculating their partition
functions presents a formidable computational obstacle to making statistical
inference. We present a model, Matérn-thinned Cox processes,
that offers computationally tractable inference for both over- and
under-dispersed patterns.
Keywords: Cox process, inference, Markov point process,
Poisson point process, thinned processes.
The manuscript will be available very soon ...
in postscript and
pdf formats.