IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v212y2024ics0167715224001196.html
   My bibliography  Save this article

Large-population asymptotics for the maximum of diffusive particles with mean-field interaction in the noises

Author

Listed:
  • Kolliopoulos, Nikolaos
  • Sanchez, David
  • Xiao, Amy

Abstract

We study the N→∞ limit of the normalized largest component in some systems of N diffusive particles with mean-field interaction. By applying a universal time change, the interaction in noises is transferred to the drift terms, and the asymptotic behavior of the maximum becomes well-understood due to existing results in the literature. We expect that the normalized maximum in the original setting has the same limiting distribution as that of i.i.d copies of a solution to the corresponding McKean–Vlasov SDE and we present some results and numerical simulations that support this conjecture.

Suggested Citation

  • Kolliopoulos, Nikolaos & Sanchez, David & Xiao, Amy, 2024. "Large-population asymptotics for the maximum of diffusive particles with mean-field interaction in the noises," Statistics & Probability Letters, Elsevier, vol. 212(C).
  • Handle: RePEc:eee:stapro:v:212:y:2024:i:c:s0167715224001196
    DOI: 10.1016/j.spl.2024.110150
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715224001196
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.spl.2024.110150?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:eee:stapro:v:212:y:2024:i:c:s0167715224001196. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.