IDEAS home Printed from https://ideas.repec.org/a/jss/jstsof/v076i03.html
   My bibliography  Save this article

Mixed Non-Parametric and Parametric Estimation Techniques in R Package etasFLP for Earthquakes' Description

Author

Listed:
  • Chiodi, Marcello
  • Adelfio, Giada

Abstract

etasFLP is an R package which fits an epidemic type aftershock sequence (ETAS) model to an earthquake catalog; non-parametric background seismicity can be estimated through a forward predictive likelihood approach, while parametric components of triggered seismicity are estimated through maximum likelihood; estimation steps are alternated until convergence is obtained and for each event the probability of being a background event is estimated. The package includes options which allow its wide use. Methods for plot, summary and profile are defined for the main output class object. The paper provides examples of the package's use with description of the underlying R and Fortran routines.

Suggested Citation

  • Chiodi, Marcello & Adelfio, Giada, 2017. "Mixed Non-Parametric and Parametric Estimation Techniques in R Package etasFLP for Earthquakes' Description," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i03).
  • Handle: RePEc:jss:jstsof:v:076:i03
    DOI: http://hdl.handle.net/10.18637/jss.v076.i03
    as

    Download full text from publisher

    File URL: https://www.jstatsoft.org/index.php/jss/article/view/v076i03/v76i03.pdf
    Download Restriction: no

    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v076i03/etasFLP_1.4.0.tar.gz
    Download Restriction: no

    File URL: https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v076i03/v76i03.R
    Download Restriction: no

    File URL: https://libkey.io/http://hdl.handle.net/10.18637/jss.v076.i03?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Giada Adelfio & Frederic Schoenberg, 2009. "Point process diagnostics based on weighted second-order statistics and their asymptotic properties," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(4), pages 929-948, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Giada Adelfio & Arianna Agosto & Marcello Chiodi & Paolo Giudici, 2021. "Financial contagion through space-time point processes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 665-688, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alexander Malinowski & Martin Schlather & Zhengjun Zhang, 2016. "Intrinsically weighted means and non-ergodic marked point processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(1), pages 1-24, February.
    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.
    3. 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.
    4. Nicoletta D’Angelo & Giada Adelfio & Jorge Mateu, 2023. "Local inhomogeneous second-order characteristics for spatio-temporal point processes occurring on linear networks," Statistical Papers, Springer, vol. 64(3), pages 779-805, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jss:jstsof:v:076:i03. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum (email available below). General contact details of provider: http://www.jstatsoft.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.