Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/74511
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Type: Journal article
Title: Multivariate analysis of an LA-ICP-MS trace element dataset for pyrite
Author: Winderbaum, L.
Ciobanu, C.
Cook, N.
Paul, M.
Metcalfe, A.
Gilbert, S.
Citation: Mathematical Geosciences, 2012; 44(7):823-842
Publisher: Kluwer Academic/Plenum Publ
Issue Date: 2012
ISSN: 1874-8961
1874-8953
Statement of
Responsibility: 
Lyron Winderbaum, Cristiana L. Ciobanu, Nigel J. Cook, Matthew Paul, Andrew Metcalfe, Sarah Gilbert
Abstract: Application 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.
Keywords: LA-ICP-MS
Pyrite
MANOVA
Parallel coordinate plots
Correlation cluster analysis
Principal component analysis
Factor analysis
Rights: © International Association for Mathematical Geosciences 2012
DOI: 10.1007/s11004-012-9418-1
Published version: http://dx.doi.org/10.1007/s11004-012-9418-1
Appears in Collections:Aurora harvest 4
Environment Institute publications
Mathematical Sciences publications

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