Skip to main content
Log in

Limiting stochastic operations for stationary spatial processes

  • Articles
  • Published:
Mathematical Geology Aims and scope Submit manuscript

Abstract

A natural extrapolation of stochastic operations (continuity and differentiation) already described in time domain (one-dimensional case) is established for spatial processes (two- or three-dimensional case). If stationarity decision is assumed, the continuity and differentiability (in the mean square sense) of a spatial process depends on the continuity and differentiability of the correlation function at the origin. Spatial processes described by stationary random functions are not continuous (in the mean square sense) when the covariance function presents a nugget effect, and they are not differentiable when the same covariance function is described by a spherical or an exponential covariance (models which are often used in geostatistics).

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Adler, R. J., 1981, The Geometry of Random Fields: John Wiley & Sons, New York, 280 p.

    Google Scholar 

  • Cramer, H., and Leadbetter, M. R., 1967, Stationary and Related Stochastic Processes: John Wiley & Sons, New York, 348 p.

    Google Scholar 

  • Journel, A. G., and Huijbregts, C. J., 1981, Mining Geostatistics: Academic Press, London, 600 p.

    Google Scholar 

  • Mandelbrot, B. B., 1975, Stochastic Models for the Earth's Relief, the Shape and the Fractal Dimension of the Coastlines, and the Number-Area Rule for Islands: Proc. Nat. Acad. Sci. USA, v. 72, p. 3825–3828.

    Google Scholar 

  • Matern, B., 1960, Spatial Variation; Comm. Swed. Forestry Res. Inst., v. 49, p. 1–144.

    Google Scholar 

  • Panda, D. P., 1977, Statistical Properties of Thresholded Images: T. R. 559, Computer Science Centre, University of Maryland, College Park.

    Google Scholar 

  • Papoulis, A., 1965, Probability, Random Variables, and Stochastic Processes: McGraw-Hill, New York, 583 p.

    Google Scholar 

  • Posa, D., 1989, Conditioning of the Stationary Kriging Matrices for Some Well-Known Covariance Models: Math. Geol., v. 21, n. 7, p. 755–765.

    Article  MathSciNet  Google Scholar 

  • Priestley, M. B., 1981, Spectral Analysis and Time Series: Academic Press, New York, 653 p.

    Google Scholar 

  • Robinson, E. A., 1967, Statistical Communication and Detection: Griffin, London.

    Google Scholar 

  • Stein, M. L. and Handcock, M. S., 1989, Some Asymptotic Properties of Kriging When the Covariance Function is Misspecified: Math. Geol., v. 21, n. 2, pp. 171–190.

    Article  Google Scholar 

  • Wong, E., 1968, Two Dimensional Random Fields and Representation of Images: SIAM J. Applied Math., v. 16, p. 756–770.

    Article  Google Scholar 

  • Yaglom, A. M., 1962, An Introduction to the Theory of Stationary Random Functions: Prentice Hall, Englewood Cliffs, New Jersey.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Posa, D. Limiting stochastic operations for stationary spatial processes. Math Geol 23, 695–702 (1991). https://doi.org/10.1007/BF02082531

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02082531

Key words

Navigation