A tool to perform a Multistatical Analysis using the Compositional Data approach and a center-log-ratio (clr) transformation for the analysis of water samples. It allows to perform hierarchical cluster analysis and to create an interactive map that includes the location of the water sample and, the assigned cluster. Based on the clustering results, representative Stiff diagrams for each cluster are built. Finally, Principal Component Analysis is used to steimate new variables called principal components as linear combinations of the original variables that maximize the variance; an interactive compositional PCA biplot is drawn allowing the identificaction of the assigned cluster, the sample name and the source type. See: Aitchison, J. (1982). <DOI:10.1111/j.2517-6161.1982.tb01195.x>The Statistical Analysis of Compositional Data. Journal of the Royal Statistical Society. Series B (Methodological), 44(2), 139–177. See: Van den Boogaart, K. G., & Tolosana-Delgado, R. (2013). <DOI:10.1007/978-3-642-36809-7 Analyzing compositional data with R. See: Piña, A., Donado, L. D., Blake, S., & Cramer, T. (2018). <DOI:10.1016/j.apgeochem.2018.05.012> Compositional multivariate statistical analysis of hydrogeochemical processes in a fractured massif: La Línea Tunnel project, Colombia. Applied Geochemistry, 95C, 1–18. See: Stiff, H. A. (1951). <DOI:10.2118/951376-G> The Interpretation of Chemical Water Analysis by Means of Patterns. Journal of Petroleum Technology, 3(10), 15–3.
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