IDEAS home Printed from https://ideas.repec.org/a/spr/metcap/v24y2022i1d10.1007_s11009-021-09863-9.html
   My bibliography  Save this article

Investigating Several Fundamental Properties of Random Lobster Trees and Random Spider Trees

Author

Listed:
  • Yuxin Ren

    (Rochester Institute of Technology)

  • Panpan Zhang

    (University of Pennsylvania)

  • Dipak K. Dey

    (University of Connecticut)

Abstract

In this paper, we investigate several random structures, namely two classes of random lobster trees (RLTs) and a class of random spider trees (RSTs). The first class of RLTs grow with a fixed probability, whereas those from the second class evolve in a dynamic manner underlying a flavor of semi-opposite reinforcement. For these two classes, we characterize the structure of the random graphs therein via some probabilistic methods. In addition, we look into a class of RSTs that evolve in a preferential attachment manner. We characterize the structure of RSTs by determining the exact and asymptotic distributions of the number of leaves, and by computing two kinds of topological indices.

Suggested Citation

  • Yuxin Ren & Panpan Zhang & Dipak K. Dey, 2022. "Investigating Several Fundamental Properties of Random Lobster Trees and Random Spider Trees," Methodology and Computing in Applied Probability, Springer, vol. 24(1), pages 431-447, March.
  • Handle: RePEc:spr:metcap:v:24:y:2022:i:1:d:10.1007_s11009-021-09863-9
    DOI: 10.1007/s11009-021-09863-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11009-021-09863-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11009-021-09863-9?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.

    References listed on IDEAS

    as
    1. Gao, Shuyang & Mahmoud, Hosam M., 2018. "A self-equilibrium Friedman-like urn via stochastic approximation," Statistics & Probability Letters, Elsevier, vol. 142(C), pages 77-83.
    Full references (including those not matched with items on IDEAS)

    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.

      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:spr:metcap:v:24:y:2022:i:1:d:10.1007_s11009-021-09863-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

      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.