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This paper aims to enhance the inference for spatial point processes’ intensity function when complex interactions among points play a crucial role. We exploit local characteristics into the inferential procedure of maximising a regularised Poisson likelihood, penalised by the degree of interaction among points. The experiments conducted emphasize the importance of local second-order characteristics in improving inference for complex spatial point processes.

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Constructed Functional Marks for Spatial Point Process Intensity Estimation

  • 会议论文

  • 发表日期：

    2025年

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  • Nicoletta D’Angelo,
  • Giada Adelfio,
  • Jorge Mateu,
  • Ottmar Cronie

摘要

This paper aims to enhance the inference for spatial point processes’ intensity function when complex interactions among points play a crucial role. We exploit local characteristics into the inferential procedure of maximising a regularised Poisson likelihood, penalised by the degree of interaction among points. The experiments conducted emphasize the importance of local second-order characteristics in improving inference for complex spatial point processes.