title: On statistical inference for the random set generated Cox process with set-marking.
abstract: Cox point process is a process class for hierarchical modelling of systems of non-interacting points in Rd under environmental heterogeneity which is modelled through a random intensity function. In this work a class of Cox processes is suggested where the random intensity is generated by a random closed set. Such heterogeneity appears for example in forestry where silvicultural treatments like harvesting and site-preparation create geometrical patterns for tree density variation in two different phases. In this paper the second order property, important both in data analysis and in the context of spatial sampling, is derived. The usefulness of the random set generated Cox process is highly increased, if for each point it is observed whether it is included in the random set or not. This additional information is easy and economical to obtain in many cases and is hence of practical value; it leads to marks for the points. The resulting random set marked Cox process is a marked point process where the marks are intensity-dependent. The problem with set-marking is that the marks are not a representative sample from the random set. This paper derives the second order property of the random set marked Cox process and suggests a practical estimation method for area fraction and covariance of the random set and for the point densities within and outside the random set. A simulated example and a forestry example are given.
authors.affiliation: Department of Mathematics and Statistics, P.O. Box 35 FIN-40014 University of Jyväskylä, Finland. penttine@maths.jyu.fi
authors.forename: Antti
authors.initials: A
authors.lastname: Penttinen
authors.forename: Aki
authors.initials: A
authors.lastname: Niemi
mesh_terms: D003198:Computer Simulation; D008954:Models, Biological; D016016:Proportional Hazards Models; D014197:Trees / Q000254:growth & development