Substationarity in Spatial Point Processes
Abstract
The goal of the article is to develop the approach of substationarity to spatial point processes (SPPs). Substationarity is a new concept, which has never been studied in the literature. It means that the distribution of SPPs can only be invariant under location shifts within a linear subspace of the domain. Theoretically, substationarity is a concept between stationariy and nonstationarity, but it belongs to nonstationarity. To formally propose the approach, the article provides the definition of substationarity and an estimation method for the first-order intensity function. As the linear subspace may be unknown, it recommends using a parametric way to estimate the linear subspace and a nonparametric way to estimate the first-order intensity function, indicating that it is a semiparametric approach. The simulation studies show that both the estimators of the linear subspace and the first-order intensity function are reliable. In an application to a forest wildfire data set, the article concludes that substationarity of wildfire occurrences may be assumed along the longitude, indicating that latitude is a more important factor than longitude in forest wildfire studies.
Keywords
Cite
@article{arxiv.1710.02864,
title = {Substationarity in Spatial Point Processes},
author = {Tonglin Zhang and Jorge Mateu},
journal= {arXiv preprint arXiv:1710.02864},
year = {2017}
}
Comments
20 pages, 3 Figures