IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v110y2016icp257-267.html
   My bibliography  Save this article

On infinite dimensional periodically correlated random fields: Spectrum and evolutionary spectra

Author

Listed:
  • Haghbin, H.
  • Shishebor, Z.

Abstract

Infinite dimensional periodically correlated (PC) random fields are studied in spectral domain. A spectral characterization is given and harmonizability is established. The covariance operator is characterized where it is observed that an infinite dimensional PC field is a two-dimensional Fourier transform of a spectral random measure. Also, an evolutionary spectral representation and a space-dependent spectral density are given.

Suggested Citation

  • Haghbin, H. & Shishebor, Z., 2016. "On infinite dimensional periodically correlated random fields: Spectrum and evolutionary spectra," Statistics & Probability Letters, Elsevier, vol. 110(C), pages 257-267.
  • Handle: RePEc:eee:stapro:v:110:y:2016:i:c:p:257-267
    DOI: 10.1016/j.spl.2015.10.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715215003466
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.spl.2015.10.003?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. Hurd, H. & Kallianpur, G. & Farshidi, J., 2004. "Correlation and spectral theory for periodically correlated random fields indexed on Z2," Journal of Multivariate Analysis, Elsevier, vol. 90(2), pages 359-383, August.
    2. H. Haghbin & Z. Shishebor & A. Soltani, 2014. "Hilbertian spatial periodically correlated first order autoregressive models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(3), pages 303-319, September.
    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.
    1. H. Haghbin & Z. Shishebor & A. Soltani, 2014. "Hilbertian spatial periodically correlated first order autoregressive models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(3), pages 303-319, September.

    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:110:y:2016:i:c:p:257-267. 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/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.