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Including covariates in a space-time point process with application to seismicity

Author

Listed:
  • Giada Adelfio

    (Università degli Studi di Palermo
    Istituto Nazionale di Geofisica e Vulcanologia (INGV))

  • Marcello Chiodi

    (Università degli Studi di Palermo
    Istituto Nazionale di Geofisica e Vulcanologia (INGV))

Abstract

The paper proposes a spatio-temporal process that improves the assessment of events in space and time, considering a contagion model (branching process) within a regression-like framework to take covariates into account. The proposed approach develops the forward likelihood for prediction method for estimating the ETAS model, including covariates in the model specification of the epidemic component. A simulation study is carried out for analysing the misspecification model effect under several scenarios. Also an application to the Italian seismic catalogue is reported, together with the reference to the developed R package.

Suggested Citation

  • Giada Adelfio & Marcello Chiodi, 2021. "Including covariates in a space-time point process with application to seismicity," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 947-971, September.
    • Handle: RePEc:spr:stmapp:v:30:y:2021:i:3:d:10.1007_s10260-020-00543-5
    DOI: 10.1007/s10260-020-00543-5
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    References listed on IDEAS

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    1. Nicoletta D’Angelo & Antonino Abbruzzo & Giada Adelfio, 2021. "Spatio-Temporal Spread Pattern of COVID-19 in Italy," Mathematics, MDPI, vol. 9(19), pages 1-14, October.
    2. Nicoletta D’Angelo & Marianna Siino & Antonino D’Alessandro & Giada Adelfio, 2022. "Local spatial log-Gaussian Cox processes for seismic data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(4), pages 633-671, December.

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