Statistical Science

Rejoinder: A Review of Self-Exciting Spatio-Temporal Point Processes and Their Applications

Alex Reinhart

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Statist. Sci., Volume 33, Number 3 (2018), 330-333.

First available in Project Euclid: 13 August 2018

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Reinhart, Alex. Rejoinder: A Review of Self-Exciting Spatio-Temporal Point Processes and Their Applications. Statist. Sci. 33 (2018), no. 3, 330--333. doi:10.1214/18-STS654.

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  • Achab, M., Bacry, E., Gaïffas, S., Mastromatteo, I. and Muzy, J.-F. (2017). Uncovering causality from multivariate Hawkes integrated cumulants. In Proceedings of the 34th International Conference on Machine Learning 70.
  • Chen, S., Witten, D. and Shojaie, A. (2017). Nearly assumptionless screening for the mutually-exciting multivariate Hawkes process. Electron. J. Stat. 11 1207–1234.
  • Eichler, M., Dahlhaus, R. and Dueck, J. (2017). Graphical modeling for multivariate Hawkes processes with nonparametric link functions. J. Time Series Anal. 38 225–242.
  • Mohler, G. O. (2014). Marked point process hotspot maps for homicide and gun crime prediction in Chicago. Int. J. Forecast. 30 491–497. DOI:10.1016/j.ijforecast.2014.01.004.
  • Oates, C. J. (2015). Accelerated non-parametrics for cascades of Poisson processes. Stat 4 183–195.
  • Ogata, Y., Matsu’ura, R. S. and Katsura, K. (1993). Fast likelihood computation of epidemic type aftershock-sequence model. Geophys. Res. Lett. 20 2143–2146. DOI:10.1029/93gl02142.
  • Xu, H., Farajtabar, M. and Zha, H. (2016). Learning granger causality for Hawkes processes. In Proceedings of the 33rd International Conference on Machine Learning (M. F. Balcan and K. Q. Weinberger, eds.). Proceedings of Machine Learning Research 48 1717–1726. PMLR, New York.
  • Zhuang, J. (2006). Second-order residual analysis of spatiotemporal point processes and applications in model evaluation. J. R. Stat. Soc. Ser. B. Stat. Methodol. 68 635–653.
  • Zhuang, J., Ogata, Y. and Vere-Jones, D. (2004). Analyzing earthquake clustering features by using stochastic reconstruction. J. Geophys. Res. 109 B05301. DOI:10.1029/2003JB002879.

See also

  • Main article: A Review of Self-Exciting Spatio-Temporal Point Processes and Their Applications.