IDEAS home Printed from https://ideas.repec.org/a/taf/jnlasa/v107y2012i497p281-289.html
   My bibliography  Save this article

Modeling Nonstationary Processes Through Dimension Expansion

Author

Listed:
  • Luke Bornn
  • Gavin Shaddick
  • James V. Zidek

Abstract

In this article, we propose a novel approach to modeling nonstationary spatial fields. The proposed method works by expanding the geographic plane over which these processes evolve into higher-dimensional spaces, transforming and clarifying complex patterns in the physical plane. By combining aspects of multidimensional scaling, group lasso, and latent variable models, a dimensionally sparse projection is found in which the originally nonstationary field exhibits stationarity. Following a comparison with existing methods in a simulated environment, dimension expansion is studied on a classic test-bed dataset historically used to study nonstationary models. Following this, we explore the use of dimension expansion in modeling air pollution in the United Kingdom, a process known to be strongly influenced by rural/urban effects, amongst others, which gives rise to a nonstationary field.

Suggested Citation

  • Luke Bornn & Gavin Shaddick & James V. Zidek, 2012. "Modeling Nonstationary Processes Through Dimension Expansion," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 281-289, March.
  • Handle: RePEc:taf:jnlasa:v:107:y:2012:i:497:p:281-289
    DOI: 10.1080/01621459.2011.646919
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01621459.2011.646919
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. repec:spr:stabio:v:9:y:2017:i:2:d:10.1007_s12561-016-9150-3 is not listed on IDEAS
    2. repec:bla:jorssc:v:66:y:2017:i:5:p:919-939 is not listed on IDEAS
    3. repec:bla:biomet:v:73:y:2017:i:3:p:759-768 is not listed on IDEAS
    4. Yi Liu & Gavin Shaddick & James V. Zidek, 0. "Incorporating High-Dimensional Exposure Modelling into Studies of Air Pollution and Health," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 0, pages 1-23.
    5. repec:eee:csdana:v:117:y:2018:i:c:p:138-153 is not listed on IDEAS
    6. Raphaƫl Huser & Marc G. Genton, 2016. "Non-Stationary Dependence Structures for Spatial Extremes," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 470-491, September.
    7. Ryan J. Parker & Brian J. Reich & Jo Eidsvik, 2016. "A Fused Lasso Approach to Nonstationary Spatial Covariance Estimation," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 569-587, September.

    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:taf:jnlasa:v:107:y:2012:i:497:p:281-289. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/UASA20 .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.