Two step estimation for Neyman-Scott point process with inhomogeneous cluster centers |
| |
Authors: | T Mrkvička M Muška J Kubečka |
| |
Institution: | 1. Department of Applied Mathematics and Informatics, Faculty of Economics, University of South Bohemia, Studentská 13, 37005, ?eské Budějovice, Czech Republic 2. Biology center of the AS CR, Institute of Hydrobiology, Na Sádkách 7, 37005, ?eské Budějovice, Czech Republic 3. Faculty of Science, University of South Bohemia, Brani?ovská 31, 37005, ?eské Budějovice, Czech Republic
|
| |
Abstract: | 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. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|