Aggregation of estimated numbers of undiscovered deposits: an R-script with an example from the Chu Sarysu Basin, Kazakhtan: Chapter B in Global mineral resource assessment
Mineral resource assessments completed by the U.S. Geological Survey during the past three decades express geologically based estimates of numbers of undiscovered mineral deposits as probability distributions. Numbers of undiscovered deposits of a given type are estimated in geologically defined regions. Using Monte Carlo simulations, these undiscovered deposit estimates are combined with tonnage and grade models to derive a probability distribution describing amounts of commodities and rock that could be present in undiscovered deposits within a study area. In some situations, it is desirable to aggregate the assessment results from several study areas. This report provides a script developed in open-source statistical software, R, that aggregates undiscovered deposit estimates of a given type, assuming independence, total dependence, or some degree of correlation among aggregated areas, given a user-specified correlation matrix.
Citation Information
Publication Year | 2011 |
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Title | Aggregation of estimated numbers of undiscovered deposits: an R-script with an example from the Chu Sarysu Basin, Kazakhtan: Chapter B in Global mineral resource assessment |
DOI | 10.3133/sir20105090b |
Authors | John H. Schuenemeyer, Michael L. Zientek, Stephen E. Box |
Publication Type | Report |
Publication Subtype | USGS Numbered Series |
Series Title | Scientific Investigations Report |
Series Number | 2010-5090 |
Index ID | sir20105090b |
Record Source | USGS Publications Warehouse |
USGS Organization | Mineral Resources Program |
Related
Upper Midwest Water Science Center - Madison, WI, Office
1 Gifford Pinchot Drive
Madison, WI 53726
United States
Michael L. Zientek, Ph.D
Emeritus (Research Geologist)
Stephen Box
Scientist Emeritus
Related
Upper Midwest Water Science Center - Madison, WI, Office
1 Gifford Pinchot Drive
Madison, WI 53726
United States