IDEAS home Printed from https://ideas.repec.org/a/eee/spapps/v130y2020i2p962-999.html
   My bibliography  Save this article

The heavy range of randomly biased walks on trees

Author

Listed:
  • Andreoletti, Pierre
  • Diel, Roland

Abstract

We focus on recurrent random walks in random environment (RWRE) on Galton–Watson trees. The range of these walks, that is the number of sites visited at some fixed time, has been studied in three different papers Andreoletti and Chen (2018), Aïdékon and de Raphélis (2017) and de Raphélis (2016). Here we study the heavy range: the number of edges frequently visited by the walk. The asymptotic behavior of this process when the number of visits is a power of the number of steps of the walk is given for all recurrent cases. It turns out that this heavy range plays a crucial role in the rate of convergence of an estimator of the environment from a single trajectory of the RWRE.

Suggested Citation

  • Andreoletti, Pierre & Diel, Roland, 2020. "The heavy range of randomly biased walks on trees," Stochastic Processes and their Applications, Elsevier, vol. 130(2), pages 962-999.
    • Handle: RePEc:eee:spapps:v:130:y:2020:i:2:p:962-999
    DOI: 10.1016/j.spa.2019.04.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304414918303739
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spa.2019.04.004?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. Comets, Francis & Falconnet, Mikael & Loukianov, Oleg & Loukianova, Dasha & Matias, Catherine, 2014. "Maximum likelihood estimator consistency for a ballistic random walk in a parametric random environment," Stochastic Processes and their Applications, Elsevier, vol. 124(1), pages 268-288.
    2. Comets, Francis & Falconnet, Mikael & Loukianov, Oleg & Loukianova, Dasha, 2016. "Maximum likelihood estimator consistency for recurrent random walk in a parametric random environment with finite support," Stochastic Processes and their Applications, Elsevier, vol. 126(11), pages 3578-3604.
    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. Chen, Xinxin, 2022. "Heavy range of the randomly biased walk on Galton–Watson trees in the slow movement regime," Stochastic Processes and their Applications, Elsevier, vol. 150(C), pages 446-509.

    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. Rémillard, Bruno N. & Vaillancourt, Jean, 2019. "Detecting periodicity from the trajectory of a random walk in random environment," Statistics & Probability Letters, Elsevier, vol. 155(C), pages 1-1.
    2. Diel, Roland & Lerasle, Matthieu, 2018. "Non parametric estimation for random walks in random environment," Stochastic Processes and their Applications, Elsevier, vol. 128(1), pages 132-155.
    3. Comets, Francis & Falconnet, Mikael & Loukianov, Oleg & Loukianova, Dasha, 2016. "Maximum likelihood estimator consistency for recurrent random walk in a parametric random environment with finite support," Stochastic Processes and their Applications, Elsevier, vol. 126(11), pages 3578-3604.
    4. Grégoire Véchambre, 2023. "Almost Sure Behavior for the Local Time of a Diffusion in a Spectrally Negative Lévy Environment," Journal of Theoretical Probability, Springer, vol. 36(2), pages 876-925, June.

    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:spapps:v:130:y:2020:i:2:p:962-999. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/505572/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.