A statistical commentary on mineral prospectivity analysis
dc.contributor.author | Baddeley, Adrian | |
dc.date.accessioned | 2018-12-13T09:13:38Z | |
dc.date.available | 2018-12-13T09:13:38Z | |
dc.date.created | 2018-12-12T02:47:04Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Baddeley, A. 2018. A statistical commentary on mineral prospectivity analysis. In Handbook of Mathematical Geosciences: Fifty Years of IAMG, 25-65. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/72523 | |
dc.identifier.doi | 10.1007/978-3-319-78999-6_2 | |
dc.description.abstract |
© Springer International Publishing AG. All rights reserved. We compare and contrast several statistical methods for predicting the occurrence of mineral deposits on a regional scale. Methods include logistic regression, Poisson point process modelling, maximum entropy, monotone regression, nonparametric curve estimation, recursive partitioning, and ROC (Receiver Operating Characteristic) curves. We discuss the use and interpretation of these methods, the relationships between them, their strengths and weaknesses from a statistical standpoint, and fallacies about them. Potential improvements and extensions include models with a flexible functional form; techniques which take account of sampling effort, deposit endowment and spatial association between deposits; conditional simulation and prediction; and diagnostics for validating the analysis. | |
dc.title | A statistical commentary on mineral prospectivity analysis | |
dc.type | Book Chapter | |
dcterms.source.startPage | 25 | |
dcterms.source.endPage | 65 | |
dcterms.source.title | Handbook of Mathematical Geosciences: Fifty Years of IAMG | |
dcterms.source.isbn | 9783319789996 | |
curtin.department | School of Electrical Engineering, Computing and Mathematical Science (EECMS) | |
curtin.accessStatus | Fulltext not available |
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