title: Structural identifiability and indistinguishability of compartmental models.
abstract: The deterministic identifiability of models is only normally considered if a problem becomes apparent in the parameter identification stage of data analysis. If no problem is perceived then the analysis will continue. However, although the problem does not become apparent, the implications of ambiguities in what is inferred from the data should be considered. This paper reviews some fundamentals with respect to model indistinguishability and parameter identifiability.
authors.affiliation: AstraZeneca R&D. Discovery DMPK, Alderley Park, Cheshire, UK. james.Yates@astrazeneca.com
authors.forename: James W T
authors.initials: JW
authors.lastname: Yates
authors.forename: R D Owen
authors.initials: RD
authors.lastname: Jones
authors.forename: Mike
authors.initials: M
authors.lastname: Walker
authors.forename: S Y Amy
authors.initials: SY
authors.lastname: Cheung