  Mineral exploration in biogeochemistry is related to the detection of
anomalies in soil, which is driven by many factors and thus a complex problem.
Mik\v{s}ov\'a, Rieser, and Filzmoser (2019) have introduced a method for the
identification of spatial patterns with increased element concentrations in
samples along a linear sampling transect. This procedure is based on fitting
Generalized Additive Models (GAMs) to the concentration data, and computing a
curvature measure from the pairwise log-ratios of these fits. The higher the
curvature, the more likely one or both elements of the pair indicate local
mineralization. This method is applied on two geochemical data sets which have
been collected specifically for the purpose of mineral exploration. The aim is
to test the technique for its ability to identify pathfinder elements to detect
mineralized zones, and to verify whether the method can indicate which sampling
material is best suited for this purpose.
  Reference: Mik\v{s}ov\'a D., Rieser C., Filzmoser P. (2019). "Identification
of mineralization in geochemistry along a transect based on the spatial
curvature of log-ratios." arXiv, (1912.02867).
