Extending compositional data analysis from a graph signal processing perspective. (arXiv:2201.10610v1 [stat.ME])

Traditional methods for the analysis of compositional data consider the
log-ratios between all different pairs of variables with equal weight,
typically in the form of aggregated contributions. This is not meaningful in
contexts where it is known that a relationship only exists between very
specific variables (e.g.~for metabolomic pathways), while for other pairs a
relationship does not exist. Modeling absence or presence of relationships is
done in graph theory, where the vertices represent the variables, and the
connections refer to …

analysis arxiv data data analysis graph perspective processing signal