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Robust principal component analysis for power transformed compositional data

Scealy, J. L.; de Caritat, Patrice; Grunsky, Eric C.; Tsagris, Michail T.; Welsh, A. H.


Geochemical surveys collect sediment or rock samples, measure the concentration of chemical elements, and report these typically either in weight percent or in parts per million (ppm). There are usually a large number of elements measured and the distributions are often skewed, containing many potential outliers. We present a new robust principal component analysis (PCA) method for geochemical survey data, that involves first transforming the compositional data onto a manifold using a relative...[Show more]

CollectionsANU Research Publications
Date published: 2015-03
Type: Journal article
Source: Journal of the American Statistical Association
DOI: 10.1080/01621459.2014.990563


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