Characterization of marked point processes by the marked correlation function

an application to forestry data


  • Wélson Antônio de Oliveira Programa de Pós-Graduação em Estatística e Experimentação Agropecuária - Universidade Federal de Lavras
  • Wigor Deivid de Melo Santos
  • José Márcio de Mello
  • João Domingos Scalon


Marked Correlation, Marked Point Processes, Spatial Dependence, Kernel Estimator


A spatial point process is understood as a set of points (events) irregularly distributed in space, generated by a stochastic probabilistic mechanism. Associating an attribute (mark) with the coordinate determines a marked point process. In the analysis of marked point processes, the interest lies in characterizing the pattern of interaction between the stochastic processes that generated the points and the marks. Analyses start with the characterization of first-order effects for a complete visualization of occurrence intensities. Assuming stationarity, a second-order analysis can be performed to characterize the spatial dependence present in the phenomenon. The data consist of georeferenced locations of occurrence of tree individuals in a native forest fragment and their respective diameters at breast height (DBH). This work aims to characterize the marked point processes by continuous variables, given by the DBH of native trees, through the estimation of the marked correlation function. All analyses were performed using the R software, developed by the R Core Team (2023). From the results, it was possible to observe the potential of the methods used to characterize the patterns and dynamics of the forest under study.


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How to Cite

Antônio de Oliveira, W., Santos, W. D. de M. ., Mello, J. M. de, & Scalon, J. D. (2024). Characterization of marked point processes by the marked correlation function: an application to forestry data. Sigmae, 12(3), 177–186. Retrieved from