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dc.contributor.authorBaddeley, Adrian
dc.contributor.authorBrown, Warick
dc.contributor.authorMilne, Robin K
dc.contributor.authorNair, Gopalan
dc.contributor.authorRakshit, Suman
dc.contributor.authorLawrence, Tom
dc.contributor.authorPhatak, Aloke
dc.contributor.authorFu, Shih Ching
dc.date.accessioned2020-12-03T13:53:35Z
dc.date.available2020-12-03T13:53:35Z
dc.date.issued2020
dc.identifier.citationBaddeley, A. and Brown, W. and Milne, R.K. and Nair, G. and Rakshit, S. and Lawrence, T. and Phatak, A. et al. 2020. Optimal Thresholding of Predictors in Mineral Prospectivity Analysis. Natural Resources Research.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/81939
dc.identifier.doi10.1007/s11053-020-09769-2
dc.description.abstract

© 2020, International Association for Mathematical Geosciences.

Some methods for analysing mineral prospectivity, especially the weights of evidence technique, require the predictor variables to be binary values. When the original evidence data are numerical values, such as geochemical indices, they can be converted to binary values by thresholding. When the evidence layer is a spatial feature such as a geological fault system, it can be converted to a binary predictor by buffering at a suitable cut-off distance. This paper reviews methods for selecting the best threshold or cut-off value and compares their performance. The review covers techniques which are well known in prospectivity analysis as well as unfamiliar techniques borrowed from other literature. Methods include maximisation of the estimated contrast, Studentised contrast, χ2 test statistic, Youden criterion, statistical likelihood, Akman–Raftery criterion, and curvature of the capture–efficiency curve. We identify connections between the different methods, and we highlight a common technical error in their application. Simulation experiments indicate that the Youden criterion has the best performance for selection of the threshold or cut-off value, assuming that a simple binary threshold relationship truly holds. If the relationship between predictor and prospectivity is more complicated, then the likelihood method is the most easily adaptable. The weights-of-evidence contrast performs poorly overall. These conclusions are supported by our analysis of data from the Murchison goldfields, Western Australia. We also propose a bootstrap method for calculating standard errors and confidence intervals for the location of the threshold.

dc.languageEnglish
dc.publisherKluwer Academic/Plenum Publishers
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/IC180100030
dc.subjectScience & Technology
dc.subjectPhysical Sciences
dc.subjectGeosciences, Multidisciplinary
dc.subjectGeology
dc.subjectAkman-Raftery criterion
dc.subjectCapture-efficiency curve
dc.subjectChange-point estimation
dc.subjectLikelihood
dc.subjectWeights of evidence
dc.subjectYouden index
dc.subjectWEIGHTS-OF-EVIDENCE
dc.subjectCHANGE-POINT ESTIMATION
dc.subjectOROGENIC GOLD DEPOSITS
dc.subjectLOGISTIC-REGRESSION
dc.subjectSPATIAL ASSOCIATION
dc.subjectMAXIMUM-LIKELIHOOD
dc.subjectPOISSON-PROCESS
dc.subjectYILGARN CRATON
dc.subjectINFERENCE
dc.subjectTIME
dc.titleOptimal Thresholding of Predictors in Mineral Prospectivity Analysis
dc.typeJournal Article
dcterms.source.issn1520-7439
dcterms.source.titleNatural Resources Research
dc.date.updated2020-12-03T13:53:35Z
curtin.note

This is a post-peer-review, pre-copyedit version of an article published in Natural Resources Research. The final authenticated version is available online at: http://doi.org/10.1007/s11053-020-09769-2

curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Sciences (EECMS)
curtin.accessStatusOpen access
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidRakshit, Suman [0000-0003-0052-128X]
curtin.contributor.orcidBaddeley, Adrian [0000-0001-9499-8382]
curtin.contributor.orcidPhatak, Aloke [0000-0002-0637-7461]
curtin.contributor.orcidFu, Shih Ching [0000-0002-9077-6026]
curtin.contributor.orcidBrown, Warick [0000-0002-8257-888X]
curtin.contributor.researcheridBaddeley, Adrian [E-3661-2010]
curtin.contributor.researcheridPhatak, Aloke [D-5166-2009]
dcterms.source.eissn1573-8981
curtin.contributor.scopusauthoridRakshit, Suman [57193350564]
curtin.contributor.scopusauthoridBaddeley, Adrian [7101639465]
curtin.contributor.scopusauthoridPhatak, Aloke [57188762833] [7005067216]
curtin.contributor.scopusauthoridFu, Shih Ching [22334071700]


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