Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/329992
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dc.contributor.CRUESPUNIVERSIDADE DE ESTADUAL DE CAMPINASpt_BR
dc.contributor.authoremailAhad.nazarpour@gmail.compt_BR
dc.typeArtigopt_BR
dc.titleStepwise Regression For Recognition Of Geochemical Anomalies: Case Study In Takab Area, Nw Iranen
dc.contributor.authorNazarpourpt_BR
dc.contributor.authorAhad; Paydarpt_BR
dc.contributor.authorGhodratolah Rostami; Carranzapt_BR
dc.contributor.authorEmmanuel John M.pt_BR
unicamp.author[Carranza, Emmanuel John M.] Univ Estadual Campinas, Inst Geosci, Campinas, SP, Brazilpt_BR
unicamp.author.external[Nazarpour, Ahadpt_BR
unicamp.author.externalPaydar, Ghodratolah Rostami] Islamic Azad Univ, Ahvaz Branch, Dept Geol, Coll Sci, Ahwaz, Iranpt_BR
unicamp.author.external[Carranza, Emmanuel John M.] James Cook Univ, Econ Geol Res Ctr, Townsville, Qld, Australiapt_BR
dc.subjectStepwise Regressionen
dc.subjectGeochemical Explorationen
dc.subjectGeochemical Anomalyen
dc.subjectLogratio Transformationen
dc.subjectTakaben
dc.description.abstractStream sediment geochemical data represent compositional materials derived from various sources, including single or multiple lithologic units, soil types, rocks types, etc. In order to delineate geochemical anomalies, stream sediment geochemical data are usually subjected to suitable multivariate analysis, and not simply using univariate threshold values because these are not reliable for delineation of geochemical anomalies in areas with complex geological units. Relationships among multiple major/trace elements and rock types are more important than single major/trace elements for delineation of geochemical anomalies. In this study we present an approach based on robust stepwise multiple regression using values major oxides (SiO2, Al2O3, Fe2O3, MnO, and MgO) in stream sediments to predict elemental content related to rock types and to recognize geochemical anomalies. The major/trace element data were subjected to isometric logratio transformation to address the compositional data closure problem. For further examination of the stepwise regression method, its performance was compared to robust principal components analysis (RPCA), median + 2MAD and concentration-area (C-A) fractal methods. The results show that multi-element anomalies obtained by the stepwise regression method, compared to those obtained by the other methods, have stronger spatial association with the known deposits, such as Chichaklo and Ay-Ghale-Si in the Takab 1:25,000 scale geological map (NW) Iran, and the anomalies have stronger spatial correlation with structural features and prospects, and thus can be used as guides to new exploration targets. (C) 2016 Elsevier B.V. All rights reserved.en
dc.relation.ispartofJournal of Geochemical Explorationpt_BR
dc.publisherElsevier Science BVpt_BR
dc.publisherAmsterdampt_BR
dc.date.issued2016pt_BR
dc.date.monthofcirculationsetpt_BR
dc.identifier.citationJournal Of Geochemical Exploration . Elsevier Science Bv, v. 168, p. 150 - 162, 2016.pt_BR
dc.language.isoEnglishpt_BR
dc.description.volume168pt_BR
dc.description.firstpage150pt_BR
dc.description.lastpage162pt_BR
dc.rightsfechadopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn0375-6742pt_BR
dc.identifier.eissn1879-1689pt_BR
dc.identifier.wosidWOS:000381648200012pt_BR
dc.identifier.doi10.1016/j.gexplo.2016.07.003pt_BR
dc.identifier.urlhttp://www.sciencedirect.com/science/article/pii/S0375674216301467pt_BR
dc.date.available2017-11-13T13:57:20Z-
dc.date.accessioned2017-11-13T13:57:20Z-
dc.description.provenanceMade available in DSpace on 2017-11-13T13:57:20Z (GMT). No. of bitstreams: 1 000381648200012.pdf: 1890587 bytes, checksum: 923641204ebc0041ffe599bc33b023b0 (MD5) Previous issue date: 2016en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/329992-
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