Home > Research > Publications & Outputs > Conditional intensity

Links

Text available via DOI:

View graph of relations

Conditional intensity: a powerful tool for modelling and analysing point process data

Research output: Contribution to journalJournal articlepeer-review

Published
<mark>Journal publication date</mark>31/03/2021
<mark>Journal</mark>Australian and New Zealand Journal of Statistics
Issue number1
Volume63
Number of pages10
Pages (from-to)83-92
Publication StatusPublished
<mark>Original language</mark>English

Abstract

The conditional intensity function of a spatial point process describes how the probability that a point of the process occurs at a particular point in its carrier space depends on the realisation of the process in the remainder of the carrier space. Provided that the point process is simple, the conditional intensity determines all of the properties of the process, in particular its likelihood function. In this paper we review the use of the conditional intensity function in the formulation of point process models and in making inferences from point process data, giving separate consideration to temporal, spatial and spatio-temporal settings. We argue that the conditional intensity function should take centre-stage in spatio-temporal point process modelling and analysis.