By John C. Davis, Ute Christina Herzfeld
This quantity vividly demonstrates the significance and lengthening breadth of quantitative equipment within the earth sciences. With contributions from a world forged of top practitioners, chapters disguise a variety of state of the art tools and purposes, together with laptop modeling and mapping innovations. Many chapters additionally include reports and vast bibliographies which serve to make this a useful advent to the total box. as well as its particular displays, the publication comprises chapters at the background of geomathematics and on R.G.V. Eigen, the ''father'' of mathematical geology. Written to commemorate the twenty fifth anniversary of the foreign organization for Mathematical Geology, the e-book may be wanted via either practitioners and researchers in all branches of geology.
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Additional info for Computers in Geology: 25 Years of Progress
Berlin, v. 2, p. 381-396. F. , 1990, Statistical pattern integration for mineral exploration, in Gaal, G. ), Computer Applications in Resource Exploration, Prediction and Assessment for Metals and Petroleum: Pergamon Press, Oxford, p. 1-21. P. G. ), Marine Minerals: Reidel, Dordrecht, p. 467-483. , 1990, The Statistical Analysis of Categorical Data: Springer-Verlag, Berlin, 523 pp. , Rangan, C. , 1981, East Pacific Rise at 21° N: The oceanic, tectonic, and hydrothermal processes of the central axis: Earth and Planetary Sci.
Weighted Logistic Regression Weights of evidence modeling and logistic regression with the observations weighted according to their areas of the corresponding unique conditions are different types of application of the loglinear model (cf. Andersen, 1990). In weighted logistic regression, the patterns are not necessarily conditionally independent as in weights of evidence modeling. 001 km2 unit cell using the same five binary patterns of Plate 3c. 054. For the most favorable unique conditions, they are nearly ten times as small as the corresponding values that resulted from applying the weights of evidence method to the five binary patterns.
In this paper, weights of evidence modeling and logistic regression are applied to occurrences of hydrothermal vents on the ocean floor, East Pacific Rise near 21° N. For comparison, logistic regression is also applied to occurrences of gold deposits in Meguma Terrane, Nova Scotia. The volcanic, tectonic, and hydrothermal processes along the central axis of the East Pacific Rise at 21° N were originally studied by Ballard et al. (1981). Their maps were previously taken as the starting point for a pilot project on estimation of the probability of occurrence of polymetallic massive sulfide deposits on the ocean floor (Agterberg and Franklin, 1987).