IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v27y2006i5p767-791.html
   My bibliography  Save this article

On Hypotheses Testing for the Selection of Spatio‐Temporal Models

Author

Listed:
  • Ana Mónica C. Antunes
  • Tata Subba Rao

Abstract

. Several models have been proposed in recent years for analysing spatial data and also, to some extent, spatio‐temporal data. One of the important problems, namely the choice of an appropriate model for describing real data sets, remains unsolved. Here we consider the analysis of spatio‐temporal processes from which observations over space and time are available. We propose statistical tests for discriminating between space–time autoregressive processes and multivariate autoregressive processes. The sampling properties of the proposed tests are considered. We illustrate the methods with a real example. We use the above tests to find the best model to describe spatio‐temporal variations of hourly carbon monoxide measurements at four locations in London in January 2004.

Suggested Citation

  • Ana Mónica C. Antunes & Tata Subba Rao, 2006. "On Hypotheses Testing for the Selection of Spatio‐Temporal Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(5), pages 767-791, September.
    • Handle: RePEc:bla:jtsera:v:27:y:2006:i:5:p:767-791
    DOI: 10.1111/j.1467-9892.2006.00488.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9892.2006.00488.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9892.2006.00488.x?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gehman, Andrew & Wei, William W.S., 2020. "Optimal spatial aggregation of space–time models and applications," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).

    More about this item

    Statistics

    Access and download statistics

    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:bla:jtsera:v:27:y:2006:i:5:p:767-791. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.