An estimating function approach to inference for inhomogeneous Neyman-Scott processes |
| |
Authors: | Waagepetersen Rasmus Plenge |
| |
Affiliation: | Institute of Mathematical Sciences, Aalborg University, Fredrik Bajersvej 7G, DK-9220 Aalborg, Denmark. rw@math.aau.dk |
| |
Abstract: | This article is concerned with inference for a certain class of inhomogeneous Neyman-Scott point processes depending on spatial covariates. Regression parameter estimates obtained from a simple estimating function are shown to be asymptotically normal when the "mother" intensity for the Neyman-Scott process tends to infinity. Clustering parameter estimates are obtained using minimum contrast estimation based on the K-function. The approach is motivated and illustrated by applications to point pattern data from a tropical rain forest plot. |
| |
Keywords: | Asymptotic normality Clustering Estimating function Infill asymptotics Inhomogeneous point process Neyman–Scott point process |
本文献已被 PubMed 等数据库收录! |