Abstract
A stationary (but not necessarily isotropic) Boolean model Y in the plane is considered as a model for overlapping particle systems. The primary grain (i.e. the typical particle) is assumed to be simply connected, but no convexity assumptions are made. A new method is presented to estimate the intensity y of the underlying Poisson process (i.e. the mean number of particles per unit area) from measurements on the union set Y. The method is based mainly on the concept of convexification of a non-convex set, it also produces an unbiased estimator for a (suitably defined) mean body of Y, which in turn makes it possible to estimate the mean grain of the particle process.
Publisher
Cambridge University Press (CUP)
Subject
Applied Mathematics,Statistics and Probability
Reference42 articles.
1. Densities for stationary random sets and point processes
2. Support functions on the convex ring in the plane and densities of random sets and point processes;Weil;Suppl. Rend. Circ. Mat. Palermo (II),1994a
3. The determination of shape and mean shape from sections and projections;Weil;Acta Stereologica,1993
4. An alternate formulation of mean value for random geometric figures*
Cited by
25 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Theory of Random Sets;Probability Theory and Stochastic Modelling;2017
2. Expectations of Random Sets;Theory of Random Sets;2017
3. Random Closed Sets and Capacity Functionals;Theory of Random Sets;2017
4. References;Stochastic Geometry and its Applications;2013-08-03
5. Estimation of the mean normal measure from flat sections;Advances in Applied Probability;2008-03