Publication at Faculty of Mathematics and Physics |
2009
Abstract
In the paper we discuss parameter estimation procedures for pla- nar point process models, which exhibit small scale clustering and large scale inhomogeneity. The interest in such models was stimulated recently by the need to analyze and availability of complex ecological datasets comming e.g. from large scale tropical rain forest studies.
Currently the most popular class of such models are the so called SOIR inhomogeneous Neyman-Scott pro- cesses. In the paper we give an overview of both the classical and recently developed estimation procedures for these processes and compare their per- formance by a simulation study.