IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v40y1998i3p267-278.html
   My bibliography  Save this article

Parametric nonstationary correlation models

Author

Listed:
  • Hughes-Oliver, Jacqueline M.
  • Gonzalez-Farias, Graciela
  • Lu, Jye-Chyi
  • Chen, Di

Abstract

Stochastic processes observed over space often exhibit nonstationarity. Possible causes of nonstationarity include mean drift, heterogeneity of responses, or a correlation pattern that is not simply a function of the Euclidean distance between two spatial locations. This paper considers the latter. The need for nonstationary correlation models has been demonstrated in several application areas, including environmental monitoring of pollutants, and modeling of semiconductor fabrication processes. We present parametric nonstationary correlation models for capturing the effect of point sources. For example, if the response variable is carbon monoxide, then a smoke stack producing carbon monoxide would be considered a point source, and it is unreasonable to believe that correlation would not depend on proximity to the smoke stack. Our parametric models allow the consideration of multiple-point sources, as well as testing the strength of a particular source. These models have the usual anisotropic and isotropic exponential correlation functions as special cases.

Suggested Citation

  • Hughes-Oliver, Jacqueline M. & Gonzalez-Farias, Graciela & Lu, Jye-Chyi & Chen, Di, 1998. "Parametric nonstationary correlation models," Statistics & Probability Letters, Elsevier, vol. 40(3), pages 267-278, October.
    • Handle: RePEc:eee:stapro:v:40:y:1998:i:3:p:267-278
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(98)00103-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Joshua L. Warren, 2020. "A Nonstationary Spatial Covariance Model for Processes Driven by Point Sources," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(3), pages 415-430, September.
    2. Victor De Oliveira, 2013. "Poisson Kriging," Working Papers 0166mss, College of Business, University of Texas at San Antonio.
    3. Jiafang Song & Joshua L. Warren, 2022. "A Directionally Varying Change Points Model for Quantifying the Impact of a Point Source," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(1), pages 46-62, March.
    4. Mark D. Ecker & Victor De Oliveira, 2007. "Bayesian Spatial Modeling of Housing Prices Subject to a Localized Externality," Working Papers 0030, College of Business, University of Texas at San Antonio.

    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:40:y:1998:i:3:p:267-278. 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: 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.