Skip to main content
Log in

Highly Robust Variogram Estimation

  • Published:
Mathematical Geology Aims and scope Submit manuscript

Abstract

The classical variogram estimator proposed by Matheron is not robust against outliers in the data, nor is it enough to make simple modifications such as the ones proposed by Cressie and Hawkins in order to achieve robustness. This paper proposes and studies a variogram estimator based on a highly robust estimator of scale. The robustness properties of these three estimators are analyzed and compared. Simulations with various amounts of outliers in the data are carried out. The results show that the highly robust variogram estimator improves the estimation significantly.

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

  • Cressie, N., 1991, Statistics for spatial data: John Wiley & Sons, New York, 900 p.

    Google Scholar 

  • Cressie, N., and Hawkins, D. M., 1980, Robust estimation of the variogram, I: Math. Geology, v. 12,no. 2, p. 115–125.

    Google Scholar 

  • Croux, C., and Rousseeuw, P. J., 1992, Time-efficient algorithms for two highly robust estimators of scale: Computational Statist., v. 1, p. 411–428.

    Google Scholar 

  • Genton, M. G., 1995, Robustesse dans l'estimation du variogramme: Bulletin de l'Institut International de Statistique, Beijing, China, v. 1, p. 400–401.

    Google Scholar 

  • Genton, M. G., and Rousseeuw, P. J., 1995, The change-of-variance function of M-estimators of scale under general contamination: Jour. Comp. Appl. Math., v. 64, p. 69–80.

    Google Scholar 

  • Hampel, F. R., 1973, Robust estimation, a condensed partial survey: Zeitschrift für Wahrscheinlichkeitstheorie und verwandte Gebiete, v. 27, p. 87–104.

    Google Scholar 

  • Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., and Stahel, W. A., 1986, Robust statistics, the approach based on influence functions: John Wiley & Sons, New York, 502 p.

    Google Scholar 

  • Huber, P. J., 1977, Robust statistical procedures: Soc. Industrial and Applied Mathematics, Philadelphia, 56 p.

    Google Scholar 

  • Huber, P. J., 1981, Robust statistics: John Wiley & Sons, New York, 308 p.

    Google Scholar 

  • Journel, A. G., and Huijbregts, Ch. J., 1978, Mining geostatistics: Academic Press, London, 600 p.

    Google Scholar 

  • Matheron, G., 1962, Traité de géostatistique appliquée, Tome I: Mémoíres du Bureau de Recherches Géologiques et Minières, no. 14, Editions Technip, Paris, 333 p.

    Google Scholar 

  • Rousseeuw, P. J., and Croux, C., 1992, Explicit scale estimators with high breakdown point, in Dodge, Y., ed., L 1 Statistical analyses and related methods: North-Holland, Amsterdam, p. 77–92.

  • Rousseeuw, P. J., and Croux, C., 1993, Alternatives to the median absolute deviation: Jour. Am. Stat. Assoc., v. 88,no. 424, p. 1273–1283.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Genton, M.G. Highly Robust Variogram Estimation. Mathematical Geology 30, 213–221 (1998). https://doi.org/10.1023/A:1021728614555

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1021728614555

Navigation