Two-Step Estimation for Modeling the Earthquake Occurrences in Sumatra by Neyman–Scott Cox Point Processes

Achmad Choiruddin*, Tabita Yuni Susanto, Rahma Metrikasari

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)

Abstract

The Cox point process is highly considered for earthquake modeling. However, the complex earthquake data which involve a large number of occurrences and geological variables often require expensive computation. This study aims to propose an efficient algorithm based on the two-step procedure by constructing the first and second order composite likelihoods. We consider four Neyman–Scott Cox process models and apply them to fit the earthquake distribution in Sumatra. We conclude that the Cauchy cluster process performs best.

Original languageEnglish
Title of host publicationSoft Computing in Data Science - 6th International Conference, SCDS 2021, Proceedings
EditorsAzlinah Mohamed, Bee Wah Yap, Jasni Mohamad Zain, Michael W. Berry
PublisherSpringer Science and Business Media Deutschland GmbH
Pages146-159
Number of pages14
ISBN (Print)9789811673337
DOIs
Publication statusPublished - 2021
Event6th International Conference on Soft Computing in Data Science, SCDS 2021 - Virtual, Online
Duration: 2 Nov 20213 Nov 2021

Publication series

NameCommunications in Computer and Information Science
Volume1489 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference6th International Conference on Soft Computing in Data Science, SCDS 2021
CityVirtual, Online
Period2/11/213/11/21

Keywords

  • Big data problem
  • Cluster point process
  • Disaster risk reduction
  • Earthquake modeling
  • Spatial point pattern

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