期刊
APPLIED GEOCHEMISTRY
卷 75, 期 -, 页码 263-276出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.apgeochem.2016.05.004
关键词
Centered log-ratio transformation; clr; Spurious correlation; Compositional data analysis
资金
- Department for Enterprise, Trade and Investment (DETINI)
- Rural Development Programme through the Northern Ireland Programme for Building Sustainable Prosperity
The complexity of modern geochemical data sets is increasing in several aspects (number of available samples, number of elements measured, number of matrices analysed, geological-environmental variability covered, etc), hence it is becoming increasingly necessary to apply statistical methods to elucidate their structure. This paper presents an exploratory analysis of one such complex data set, the Tellus geochemical soil survey of Northern Ireland (NI). This exploratory analysis is based on one of the most fundamental exploratory tools, principal component analysis (PCA) and its graphical representation as a biplot, albeit in several variations: the set of elements included (only major oxides vs. all observed elements), the prior transformation applied to the data (none, a standardization or a logratio transformation) and the way the covariance matrix between components is estimated (classical estimation vs. robust estimation). Results show that a log-ratio PCA (robust or classical) of all available elements is the most powerful exploratory setting, providing the following insights: the first two processes controlling the whole geochemical variation in NI soils are peat coverage and a contrast between mafic and felsic background lithologies; peat covered areas are detected as outliers by a robust analysis, and can be then filtered out if required for further modelling; and peat coverage intensity can be quantified with the %Br in the subcomposition (Br, Rb, Ni). (C) 2016 Elsevier Ltd. All rights reserved.
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