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An Inhomogeneous Weibull–Hawkes Process to Model Underdispersed Acoustic Cues

Author

Listed:
  • Alec B. M. Van Helsdingen

    (University of Auckland)

  • Tiago A. Marques

    (University of St Andrews
    Faculdade de Ciências, Universidade de Lisboa)

  • Charlotte M. Jones-Todd

    (University of Auckland)

Abstract

A Hawkes point process describes self-exciting behaviour where event arrivals are triggered by historic events. These models are increasingly becoming a popular choice in analysing event-type data. Like all other inhomogeneous Poisson point processes, the waiting time between events in a Hawkes process is derived from an exponential distribution with mean one. However, as with many ecological and environmental data, this is an unrealistic assumption. We, therefore, extend and generalise the Hawkes process to account for potential under- or overdispersion in the waiting times between events by assuming the Weibull distribution as the foundation of the waiting times. We apply this model to the acoustic cue production times of sperm whales and show that our Weibull–Hawkes model better captures the inherent underdispersion in the interarrival times of echolocation clicks emitted by these whales.

Suggested Citation

  • Alec B. M. Van Helsdingen & Tiago A. Marques & Charlotte M. Jones-Todd, 2025. "An Inhomogeneous Weibull–Hawkes Process to Model Underdispersed Acoustic Cues," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 30(1), pages 39-62, March.
  • Handle: RePEc:spr:jagbes:v:30:y:2025:i:1:d:10.1007_s13253-024-00626-w
    DOI: 10.1007/s13253-024-00626-w
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    References listed on IDEAS

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    1. Earvin Balderama & Frederic Paik Schoenberg & Erin Murray & Philip W. Rundel, 2012. "Application of Branching Models in the Study of Invasive Species," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 467-476, June.
    2. Kristensen, Kasper & Nielsen, Anders & Berg, Casper W. & Skaug, Hans & Bell, Bradley M., 2016. "TMB: Automatic Differentiation and Laplace Approximation," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 70(i05).
    3. Emmanuel Bacry & Iacopo Mastromatteo & Jean-Franc{c}ois Muzy, 2015. "Hawkes processes in finance," Papers 1502.04592, arXiv.org, revised May 2015.
    4. S. H. Ong & Atanu Biswas & S. Peiris & Y. C. Low, 2015. "Count Distribution for Generalized Weibull Duration with Applications," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(19), pages 4203-4216, October.
    5. Jiancang Zhuang & Jorge Mateu, 2019. "A semiparametric spatiotemporal Hawkes‐type point process model with periodic background for crime data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(3), pages 919-942, June.
    6. Nikos Yannaros, 1994. "Weibull renewal processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 46(4), pages 641-648, December.
    7. Junhyung Park & Frederic Paik Schoenberg & Andrea L. Bertozzi & P. Jeffrey Brantingham, 2021. "Investigating Clustering and Violence Interruption in Gang-Related Violent Crime Data Using Spatial–Temporal Point Processes With Covariates," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1674-1687, October.
    8. Alan G. Hawkes, 2018. "Hawkes processes and their applications to finance: a review," Quantitative Finance, Taylor & Francis Journals, vol. 18(2), pages 193-198, February.
    9. Marj Tonini & Mário Gonzalez Pereira & Joana Parente & Carmen Vega Orozco, 2017. "Evolution of forest fires in Portugal: from spatio-temporal point events to smoothed density maps," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(3), pages 1489-1510, February.
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