Nonrenewable Resources

, Volume 6, Issue 1, pp 11–25 | Cite as

Additive models in mining and exploration



In this paper we present the use of additive models (AMs) for geostatistical applications. AMs are generalizations of linear regression models which hold the central place in the toolbox of applied statisticians. Generally speaking, the linear relationship between response and predictors is replaced with a general functional form. Recently such models were introduced in geostatistics. Especially, we give an approach for binary data. In this case we get generalized additive models (GAMs). Logistic regression is quite popular in medical and biological research. Using logit links also in GAMs we get so called additive logistic models. An application for geostatistical data is introduced. In a second approach we use AMs for spatial prediction and surface modelling. In both cases an advantage of multivariate data can be taken. The proposed applications can be used in the development of exploration strategies, especially in the early stage of exploration

Key words

Additive models regression geostatistics kriging spatial statistics 


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  1. Adler, R. J., 1981, The geometry of random fields: Chichester, John Wiley & Sons, 280 p.Google Scholar
  2. Carr, J. R., 1994, Order relation correction experiments for probability kriging: Mathematical Geology, v. 26, no. 5, p. 605–621.Google Scholar
  3. Chambers, J. M. and Hastie, T. J., 1993, Statistical Modelsin S: London, Chapman & Hall, 608 p.Google Scholar
  4. Cressie, N. A. C, 1993, Statistics for spatial data (revised edition): New York, NY, John Wiley & Sons, 900 p.Google Scholar
  5. Hastie, T. J. and Tibshirani, R. J., 1990, Generalized additive models: London, Chapman & Hall, 335 p.Google Scholar
  6. Pilz, J., 1995, Neuere Methoden der Trendmodelliemng, Interpola- tion und Meßnetzplanung zur Auswertung von Umweltdaten,in 4. Jahrestagung der Deutschen Gesellschaft für Mathema- tische Geologie und Geoinformatik, Bochum, Germany, 8–9 March 1995. [in German].Google Scholar
  7. Ripley, B. D., 1981, Spatial statistics: New York, NY, John Wiley & Sons, 252 p.Google Scholar
  8. Venables, W. N. and Ripley, B. D., 1994, Modern applied statistics with S-Plus: Berlin, Springer-Verlag, 462 p.Google Scholar
  9. Wälder, K., in press, 1997, Geostatistische Erkundungsstrategien: ein entscheidungstheoretischer Ansatz: Das Markscheide- wesen. [In German].Google Scholar

Copyright information

© International Association for Mathematical Geology 1997

Authors and Affiliations

  1. 1.Graduate college for spatial statisticsFreiberg University of Mining and TechnologyFreibergGermany

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