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

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Soft Computing in Data Science (SCDS 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1489))

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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.

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Acknowledgements

The research is supported by Institut Teknologi Sepuluh Nopember grant number 1292/PKS/ITS/2021. We thank the two reviewers for the comments.

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Authors and Affiliations

  1. Department of Statistics, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia

    Achmad Choiruddin, Tabita Yuni Susanto & Rahma Metrikasari

Authors
  1. Achmad Choiruddin
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  2. Tabita Yuni Susanto
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  3. Rahma Metrikasari
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Corresponding author

Correspondence to Achmad Choiruddin .

Editor information

Editors and Affiliations

  1. Universiti Teknologi MARA, Shah Alam, Malaysia

    Azlinah Mohamed

  2. Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia

    Bee Wah Yap

  3. Universiti Teknologi MARA, Shah Alam, Malaysia

    Jasni Mohamad Zain

  4. University of Tennessee, Knoxville, TN, USA

    Michael W. Berry

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Choiruddin, A., Susanto, T.Y., Metrikasari, R. (2021). Two-Step Estimation for Modeling the Earthquake Occurrences in Sumatra by Neyman–Scott Cox Point Processes. In: Mohamed, A., Yap, B.W., Zain, J.M., Berry, M.W. (eds) Soft Computing in Data Science. SCDS 2021. Communications in Computer and Information Science, vol 1489. Springer, Singapore. https://doi.org/10.1007/978-981-16-7334-4_11

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  • DOI: https://doi.org/10.1007/978-981-16-7334-4_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-7333-7

  • Online ISBN: 978-981-16-7334-4

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