Skip to main content

A Spectral Test of Nonstationarity for Spatial Processes

  • Conference paper
geoENV IV — Geostatistics for Environmental Applications

Part of the book series: Quantitative Geology and Geostatistics ((QGAG,volume 13))

Abstract

We present a test for the detection of nonstationary spatial processes using spectral methods. The spatial field is represented locally as a stationary isotropic random field, but only the parameters of the stationary random field that describe the behaviour of the process at high frequencies are allowed to vary across in space, reflecting the lack of stationarity of the process.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cressie, N.A.C. (1993). Statistics for Spatial Data, Wiley, Revised version.

    Google Scholar 

  2. Dempster, A.P. and Schatzoff, M. (1965). Expected Significance Level as a sensitivity index for test statistics. Journal of the American Statistical Association, 60:420–436.

    Google Scholar 

  3. Fuentes, M. (2001). A high frequency kriging approach for nonstationary environmental processes. Environmetrics, 12:469–483.

    Article  Google Scholar 

  4. Fuentes, M. (2002). Spectral methods for nonstationary spatial processes. Biometrika, 89. To appear.

    Google Scholar 

  5. Fuentes, M. and Smith, R. (2002). A new class of models for nonstationary processes. Submitted.

    Google Scholar 

  6. Rao, C.R. (1973). Linear Statistical Inference and its Applications. 2nd Edition, Wiley, New York.

    Google Scholar 

  7. Renshaw, E. (2002). Two-dimensional spectral analysis for marked point processes. Biometrical Journal, 6:718–745.

    Google Scholar 

  8. Sampson, P. and Guttorp, P. (1992). Nonparametric estimation of nonstationary spatial covariance structure. Journal of American Statistical Association, 87:108–119.

    Google Scholar 

  9. Stein, M. (1999). Interpolation of Spatial Data: some theory for kriging. Springer-Verlag, New York.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Kluwer Academic Publishers

About this paper

Cite this paper

Mateu, J., Juan, P. (2004). A Spectral Test of Nonstationarity for Spatial Processes. In: Sanchez-Vila, X., Carrera, J., Gómez-Hernández, J.J. (eds) geoENV IV — Geostatistics for Environmental Applications. Quantitative Geology and Geostatistics, vol 13. Springer, Dordrecht. https://doi.org/10.1007/1-4020-2115-1_29

Download citation

  • DOI: https://doi.org/10.1007/1-4020-2115-1_29

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-2007-0

  • Online ISBN: 978-1-4020-2115-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics