IDEAS home Printed from https://ideas.repec.org/a/spr/jotpro/v34y2021i1d10.1007_s10959-019-00964-3.html
   My bibliography  Save this article

Hausdorff Measure of the Range of Space–Time Anisotropic Gaussian Random Fields

Author

Listed:
  • Wenqing Ni

    (Zhejiang Gongshang University
    Jimei University)

  • Zhenlong Chen

    (Zhejiang Gongshang University)

Abstract

Let $$X=\{X(t)\in {{\mathbb {R}}}^d, t\in {{\mathbb {R}}}^N\}$$ X = { X ( t ) ∈ R d , t ∈ R N } be a centered space–time anisotropic Gaussian random field with stationary increments, whose components are independent but may not be identically distributed. Under certain mild conditions, we determine the exact Hausdorff measure function for the range $$X([0,1]^N)$$ X ( [ 0 , 1 ] N ) . Our result extends those in Talagrand (Ann Probab 23:767–775, 1995) for fractional Brownian motion and Luan and Xiao (J Fourier Anal Appl 18:118–145, 2012) for time-anisotropic and space-isotropic Gaussian random fields.

Suggested Citation

  • Wenqing Ni & Zhenlong Chen, 2021. "Hausdorff Measure of the Range of Space–Time Anisotropic Gaussian Random Fields," Journal of Theoretical Probability, Springer, vol. 34(1), pages 264-282, March.
  • Handle: RePEc:spr:jotpro:v:34:y:2021:i:1:d:10.1007_s10959-019-00964-3
    DOI: 10.1007/s10959-019-00964-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10959-019-00964-3
    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/s10959-019-00964-3?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. Ni, Wenqing & Chen, Zhenlong, 2016. "Hitting probabilities of a class of Gaussian random fields," Statistics & Probability Letters, Elsevier, vol. 118(C), pages 145-155.
    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. Weijie Yuan & Zhenlong Chen, 2024. "Hausdorff Measure and Uniform Dimension for Space-Time Anisotropic Gaussian Random Fields," Journal of Theoretical Probability, Springer, vol. 37(3), pages 2304-2329, September.

    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:jotpro:v:34:y:2021:i:1:d:10.1007_s10959-019-00964-3. 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.