IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v69y2020i1p47-67.html
   My bibliography  Save this article

Zoom‐in–out joint graphical lasso for different coarseness scales

Author

Listed:
  • Eugen Pircalabelu
  • Gerda Claeskens
  • Lourens J. Waldorp

Abstract

A new method is proposed to estimate graphical models simultaneously from data obtained at different coarseness scales. Starting from a predefined scale the method offers the possibility to zoom in or out over scales on particular edges. The estimated graphs over the different scales have similar structures although their level of sparsity depends on the scale at which estimation takes place. The method makes it possible to evaluate the evolution of the graphs from the coarsest to the finest scale or vice versa. We select an optimal coarseness scale to be used for further analysis. Simulation studies and an application on functional magnetic resonance brain imaging data show the method's performance in practice.

Suggested Citation

  • Eugen Pircalabelu & Gerda Claeskens & Lourens J. Waldorp, 2020. "Zoom‐in–out joint graphical lasso for different coarseness scales," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(1), pages 47-67, January.
  • Handle: RePEc:bla:jorssc:v:69:y:2020:i:1:p:47-67
    DOI: 10.1111/rssc.12378
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rssc.12378
    Download Restriction: no

    File URL: https://libkey.io/10.1111/rssc.12378?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
    ---><---

    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:bla:jorssc:v:69:y:2020:i:1:p:47-67. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.