Abstract
A recent paper published in PLOS Computational Biology [1] introduces the Scaling Invariance Method (SIM) for analysing structural local identifiability and observability. These two properties define mathematically the possibility of determining the values of the parameters (identifiability) and states (observability) of a dynamic model by observing its output. In this note we warn that SIM considers scaling symmetries as the only possible cause of non-identifiability and non-observability. We show that other types of symmetries can cause the same problems without being detected by SIM, and that in those cases the method may lead one to conclude that the model is identifiable and observable when it is actually not.
Highlights
It should be noted that structural local identifiability and observability are properties that hold for almost all points in parameter or state space—that is, with the possible exception of a subset of measure zero
These properties may not hold for all the possible input vectors—the above definitions entail that at least a subset of the admissible inputs is sufficiently exciting for that purpose
We show the calculations of the Scaling Invariance Method (SIM) test below
Summary
Citation: Villaverde AF, Massonis G (2021) On testing structural identifiability by a simple scaling method: Relying on scaling symmetries can be misleading. PLoS Comput Biol 17(10): e1009032. https://doi.org/10.1371/journal.pcbi.1009032 Funding: AFV has received funding from a Ramon y Cajal Fellowship (RYC-2019-027537-I) and from the Spanish Ministry of Science, Innovation and Universities and the European Union FEDER under project grant SYNBIOCONTROL (DPI2017-82896C2-2-R). GM was funded by the CSIC intramural project grant MOEBIUS (PIE 202070E062). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.
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