Multidimensional Scaling of Varietal Data in Sedimentary Provenance Analysis

Varietal studies of sedimentary provenance use the properties individual minerals or mineral groups. These are recorded as lists numerical tables that can be difficult to interpret. Multidimensional Scaling (MDS) is a popular multivariate ordination technique for analyzing other types data based on, example, detrital geochronology petrography. Applying MDS varietal would allow them treated on an equal footing with those proxies. requires method quantify dissimilarity between two samples. This paper introduces three ways do so. The first (“treatment-by-row”) turns (compositional) into vectors, using principal component analysis. vectors then “distributional” and subjected analysis measures such Kolmogorov-Smirnov statistic. second (“treatment-by-column”) compositional multiple each representing single data. distributional sets subsequently Procrustes 3-way MDS. third uses Wasserstein-2 distance jointly compare rows columns arguably makes best but acts more like “black box” than methods. methods titanite set from Colombia yields similar results. After converting matrices, they combined data, again