J. Dvořák (2011)
On moment estimation methods for spatial Cox processes
WDS'11 Proceedings of Contributed Papers: Part I - Mathematics and Computer Sciences (eds. J. Šafránková and J. Pavlů), Prague, Matfyzpress, 31-36.
Large data sets in the form of point patterns are frequently encountered in practice and need to be analyzed, e.g. by fitting parametric models. We consider stationary spatial Cox point processes and give overview of moment estimation methods suitable for fitting this class of models to the data – the minimum contrast method and the composite likelihood and the Palm likelihood approaches. These methods represent a simulation-free faster-to-compute alternative to the computationally intense maximum likelihood estimation.