Visualization and modeling of subpopulations of fumarolic fluids based on chemical components: a statistical approach

In the investigation of fluid samples of a volcanic system, collected during a given period of time, one of the main goals is to discover cause–effect relationships that allow us to explain changes in the chemical composition. They might be caused by physicochemical factors, such as temperature, pressure, or non-conservative behavior of some chemical constituents (addition or subtraction of material), among others. The presence of subgroups of observations showing different behavior is evidence of unusually complex situations, which might render even more difficult the analysis and interpretation of observed phenomena. These cases require appropriate statistical techniques as well as sound a priori hypothesis concerning underlying geological processes. The purpose of this article is to present the state of the art in the methodology for a better visualization of compositional data, as well as for detecting statistically significant sub-populations.