Dynamic-network identifiability
Research context
research method · established · As of 2026-10-10
A model is structurally unidentifiable when distinct parameter values cannot be distinguished even with ideal observations; practical unidentifiability can remain because actual observations are limited.
Key knowledge
A model is structurally unidentifiable when distinct parameter values cannot be distinguished even with ideal observations; practical unidentifiability can remain because actual observations are limited. Profile likelihood can diagnose uncertainty and guide discriminating experiments.
Conditions and scope
- Conclusions depend on observed variables, stimulus and model structure; a low fitting residual is not evidence that each rate was identified.
Sources · 1
References
Sources retain their recorded scope. A source link alone does not establish verification of every statement.
Evidence and review
Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood: Original abstract: structural/practical distinction and confidence intervals (indexed author abstract)
2026-10-10 · Bounded author source inspection of dynamic-network identifiability, including the stated conditions; independent branch review is recorded separately.
Entry details
Permanent link to this entry ↗- Record identity
- res-bio-network-identifiability
- Revision
- research.1
- Structured reference record
- Postgraduate & research reference