Three nonparametric techniques for the optimum discretization of quantitative geological variables |
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| Authors: | Guocheng Pan and DeVerle P. Harris |
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| Affiliation: | (1) Mineral Resources Estimation and Mineral Economics, Department of Mining and Geological Engineering, University of Arizona, 85721 Tucson, Arizona;(2) Department of Mining and Geological Engineering, University of Arizona, 85721 Tucson, Arizona |
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| Abstract: | Three nonparametric techniques for the optimum discretization of quantitative geological features are proposed and demonstrated. The three methods are: isolated weight, entropy information, and rank correlation. Optimum discretization plays important roles in solutions to the following geoscience problems: (1) signal/noise separation and delineation of meaningful anomalies and other geofields related to mineral targets; (2) selection of those geological variables that explain variations in mineral resources; (3) determination of the best subintervals of values for a variable with respect to mineralization; (4) enhancement of certain complex and concealed information of a geofeature about its correlation with magnitude of mineralization; and (5) unification of diverse geodata so that these data can be integrated and analyzed. |
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| Keywords: | optimum discretization isolated weight entropy information rank correlation Nb-Ta deposit Au-Ag deposit exploration target |
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