Second-order analysis of space-time clustering.
We consider the problem of detecting and describing space-time interaction in point process data. We extend existing second-order methods for purely spatial point process data to the spatial-temporal setting. This extension allows us to estimate space-time interaction as a function of spatial and temporal separation, and provides a useful reinterpretation of a popular test, due to Knox, for space-time interaction. Applications to simulated and real data indicate the method's potential.
Diggle
P J
PJ
Department of Mathematics and Statistics, Lancaster University, UK.
Chetwynd
A G
AG
Häggkvist
R
R
Morris
S E
SE
D016000:Cluster Analysis; D003625:Data Collection; D004196:Disease Outbreaks / Q000706:statistics & numerical data; D004812:Epidemiologic Methods; D006801:Humans; D015233:Models, Statistical; D009010:Monte Carlo Method; D012307:Risk Factors