"Stationary" point processes are uncommon on linear networks

Adrian Baddeley, Gopalan Nair, Suman Rakshit, Gregory McSwiggan

Research output: Contribution to journalArticlepeer-review

30 Citations (Web of Science)

Abstract

Statistical methodology for analysing patterns of points on a network of lines, such as road traffic accident locations, often assumes that the underlying point process is "stationary" or "correlation-stationary." However, such processes appear to be rare. In this paper, popular procedures for constructing a point process are adapted to linear networks: many of the resulting models are no longer stationary when distance is measured by the shortest path in the network. This undermines the rationale for popular statistical methods such as the K-function and pair correlation function. Alternative strategies are proposed, such as replacing the shortest-path distance by another metric on the network.

Original languageEnglish
Pages (from-to)68-78
Number of pages11
JournalStat
Volume6
Issue number1
DOIs
Publication statusPublished - 8 Feb 2017

Fingerprint

Dive into the research topics of '"Stationary" point processes are uncommon on linear networks'. Together they form a unique fingerprint.

Cite this