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Graphical modelling and partial characteristics for multitype and multivariate-marked spatio-temporal point processes

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  • Eckardt, Matthias
  • González, Jonatan A.
  • Mateu, Jorge

Abstract

A method for dealing with multivariate analysis of marked spatio-temporal point processes is presented by introducing different partial point characteristics, and by extending the spatial dependence graph model formalism. The approach yields a unified framework for different types of spatio-temporal data, including both, purely qualitatively (multivariate) cases and multivariate cases with additional quantitative marks. The proposed graphical model is defined through partial spectral density characteristics; it is highly computationally efficient and reflects the conditional similarity amongst sets of spatio-temporal sub-processes of either points or marked points with identical discrete marks. Two applications, on crime and forestry data, are presented.

Suggested Citation

  • Eckardt, Matthias & González, Jonatan A. & Mateu, Jorge, 2021. "Graphical modelling and partial characteristics for multitype and multivariate-marked spatio-temporal point processes," Computational Statistics & Data Analysis, Elsevier, vol. 156(C).
    • Handle: RePEc:eee:csdana:v:156:y:2021:i:c:s0167947320302309
    DOI: 10.1016/j.csda.2020.107139
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    References listed on IDEAS

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