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arXiv · 2608.12510

Bayesian Modeling of Gibbs Point Processes via Basis Function Expansions

Christopher Hassett·Athanasios C. Micheas·Scott H. Holan·Stamatis Dostoglou
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Abstract

We present a hierarchical Bayesian framework for non-homogeneous pairwise interaction Gibbs point process models, where the global and local effect functions are modeled via basis function expansions. We further propose a testing procedure in order to assess complete spatial randomness. The proposed methodology is exemplified through two real benchmark data examples involving water striders and forest fires.

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Christopher Hassett, Athanasios C. Micheas, Scott H. Holan, Stamatis Dostoglou. 2026-08-12. Bayesian Modeling of Gibbs Point Processes via Basis Function Expansions. https://arxiv.org/abs/2608.12510

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