English

Functional marked point processes -- A natural structure to unify spatio-temporal frameworks and to analyse dependent functional data

Statistics Theory 2019-12-02 v1 Computation Methodology Statistics Theory

Abstract

This paper treats functional marked point processes (FMPPs), which are defined as marked point processes where the marks are random elements in some (Polish) function space. Such marks may represent e.g. spatial paths or functions of time. To be able to consider e.g. multivariate FMPPs, we also attach an additional, Euclidean, mark to each point. We indicate how FMPPs quite naturally connect the point process framework with both the functional data analysis framework and the geostatistical framework. We further show that various existing models fit well into the FMPP framework. In addition, we introduce a new family of summary statistics, weighted marked reduced moment measures, together with their non-parametric estimators, in order to study features of the functional marks. We further show how they generalise other summary statistics and we finally apply these tools to analyse population structures, such as demographic evolution and sex ratio over time, in Spanish provinces.

Keywords

Cite

@article{arxiv.1911.13142,
  title  = {Functional marked point processes -- A natural structure to unify spatio-temporal frameworks and to analyse dependent functional data},
  author = {Ottmar Cronie and Mohammad Ghorbani and Jorge Mateu and Jun Yu},
  journal= {arXiv preprint arXiv:1911.13142},
  year   = {2019}
}

Comments

44 pages, 3 figures with 9 plots

R2 v1 2026-06-23T12:31:07.013Z