Two step estimation for Neyman-Scott point process with inhomogeneous cluster centers
- First Online:
- Cite this article as:
- Mrkvička, T., Muška, M. & Kubečka, J. Stat Comput (2014) 24: 91. doi:10.1007/s11222-012-9355-3
- 386 Views
This paper is concerned with parameter estimation for the Neyman-Scott point process with inhomogeneous cluster centers. Inhomogeneity depends on spatial covariates. The regression parameters are estimated at the first step using a Poisson likelihood score function. Three estimation procedures (minimum contrast method based on a modified K function, composite likelihood and Bayesian methods) are introduced for estimation of clustering parameters at the second step. The performance of the estimation methods are studied and compared via a simulation study. This work has been motivated and illustrated by ecological studies of fish spatial distribution in an inland reservoir.