ArticleEntropy (Basel, Switzerland)2025
Coarse-Grained Hawkes Processes.
Article in Entropy (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
When analyzing real-world event data, it is often the case that bin-count processes are observed instead of precise event time-stamps along a continuous timeline, owing to practical limitations in measurement accuracy. In this work, we propose a modeling framework for aggregated event data generated by multivariate Hawkes processes. The introduced model, termed the coarse-grained Hawkes process, effectively captures the second-order statistical characteristics of the bin-count representation of the Hawkes process, particularly when the bin size is large relative to the typical support of the excitation kernel. Building upon this model, we develop a method for inferring the underlying Hawkes process from bin-count observations, and demonstrate through simulation studies that the proposed approach performs comparably to, or even surpasses, existing techniques, while maintaining computational efficiency in parameter estimation.
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