Waagepetersen, Rasmus Plenge

This paper 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.“This paper 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

VBN (Videnbasen)  Aalborg Universitets forskningsportal

An estimating function approach to inference for inhomogeneous Neyman-Scott processes

http://vbn.aau.dk/files/526459/R-2005-30.pdf

An estimating function approach to inference for inhomogeneous Neyman-Scott processes

Abstract

Similar works

Full text

Available Versions

VBN (Videnbasen) Aalborg Universitets forskningsportal