Multivariate analysis of an LA-ICP-MS trace element dataset for pyrite
journal contribution
posted on 2023-05-17, 15:49 authored by Winderbaum, L, Ciobanu, CL, Cook, NJ, Paul, M, Metcalfe, A, Gilbert, SApplication of multivariate statistics to trace element datasets is reviewed using 164 multi-element LA-ICP-MS spot analyses of pyrite from the Moonlight epithermal gold prospect, Queensland, Australia. Multivariate analysis of variance (MANOVA) is used to demonstrate that classification of pyrite on morphological and other non-numeric factors is geochemically valid. Parallel coordinate plots and correlation cluster analysis using Spearman's coefficients are used to discover unexpected elemental relationships without making assumptions a priori. Finally, principal component analysis and factor analysis are used to demonstrate the presence of sub-classes of pyrite. Corroborated with geological data, statistical analysis provides evidence for successive generations of hydrothermal fluids, each introducing specific metals, and for partial or complete replacement of different minerals. The data permit reinterpretation of Moonlight as a telescoped system where epithermal-Au (± base metals) is superposed onto early porphyry-Mo mineralization. © 2012 International Association for Mathematical Geosciences.
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Publication title
Mathematical GeosciencesVolume
44Issue
7Pagination
823-842ISSN
1874-8961Department/School
School of Natural SciencesPublisher
SpringerPlace of publication
Tiergartenstr 17, Heidelberg, 69121 GermanyRights statement
Copyright 2012 International Association for Mathematical Geosciences.Repository Status
- Restricted
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