Abstract
In statistical seismology, we can use stochastic process to explain random natural phenomena. One area of study in stochastic processes is point process. At a point process, earthquakes are viewed as a collection of random points in a space, where each point represents the time or/and location of an earthquake. In stochastic epidemic type model earthquake occurrence is assumed as an epidemic, i.e. a large earthquake triggers aftershocks at a certain time interval and the impact may extend to a region. By using point process approach, a stochastic model can be presented with its conditional intensity function, that is the probability of earthquake occurrence per time unit. It is expected that the analysis on the conditional intensity function of the epidemic type model provides information about the probability of earthquake occurrence based on its history. We apply the model to analyze seismic activity in Java Island, Indonesia.
Supported by the Ministry of Research, Technology, and Higher Education of the Republic of Indonesia through Grant of Pascadoctor No. 474/UN27.21/PP/2018.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Katili, J.A.: Plate tectonics of indonesia with special reference to the Sundaland area. In: Proceedings Indonesian Petroleum Association (IPA) (1972)
Ogata, Y.: Statistical models for earthquake occurrences and residual analysis for point processes. J. Am. Stat. Assoc. 83, 9–27 (1988)
Ogata, Y., Zhuang, J.: Space-time ETAS models and an improved extension. Tectonophysics 413(1–2), 13–23 (2006)
Pratiwi, H., Slamet, I., Saputro, D.R.S.: Respatiwulan: self-exciting point process in modeling earthquake occurrences. J. Phys. Conf. Ser. 855, 012033 (2017)
Soehaimi, A.: Seismotektonik dan Potensi Kegempaan Wilayah Jawa. Pusat Survei Geologi, Bandung 3 (2008)
Schoenberg, F.P., Brillinger, D.R., Guttorp, P.: Point processes, spatial-temporal. Encycl. Environ. 3, 1573–1577 (2002)
Utsu, T.: Aftershock and earthquake statistics (I). J. Fac. Sci. Hokkaido Univ. 3, 129–195 (1969)
Veen, A., Schoenberg, F.P.: Estimation of space-time branching process model in seismology using an EM-type algorithm. J. Am. Stat. Assoc. 103(482), 614–624 (2008)
Zhuang, J., Ogata, Y., Vere-Jones, D.: Stochastic declustering of space-time earthquake occurences. J. Am. Stat. Assoc. 97(458), 369–380 (2002)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Pratiwi, H., Priambodo, D.C., Respatiwulan, Mangku, I.W. (2018). Stochastic Epidemic Type Model for Analyzing Seismic Activity. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10960. Springer, Cham. https://doi.org/10.1007/978-3-319-95162-1_49
Download citation
DOI: https://doi.org/10.1007/978-3-319-95162-1_49
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-95161-4
Online ISBN: 978-3-319-95162-1
eBook Packages: Computer ScienceComputer Science (R0)