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Global approaches to identifiability testing for linear and nonlinear state space models

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  • Walter, Eric
  • Lecourtier, Yves

Abstract

Whenever a model is not identifiable, there exist several parameter vectors θ which yield the same input-output behavior, so that any further interprtation of θ is questionable. In this paper two methods which can be used to test state-space models for identifiability with a global approach are presented. While the first one is useful for nonlinear and/or time-varying models, the second one is suitable for linear time-invariant models. An appendix provides tools for the solution of he sets of polynomial equations involved in both methods.

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  • Walter, Eric & Lecourtier, Yves, 1982. "Global approaches to identifiability testing for linear and nonlinear state space models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 24(6), pages 472-482.
    • Handle: RePEc:eee:matcom:v:24:y:1982:i:6:p:472-482
    DOI: 10.1016/0378-4754(82)90645-0
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    Cited by:

    1. Kocięcki, Andrzej & Kolasa, Marcin, 2023. "A solution to the global identification problem in DSGE models," Journal of Econometrics, Elsevier, vol. 236(2).
    2. Walter, Eric & Pronzato, Luc, 1996. "On the identifiability and distinguishability of nonlinear parametric models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 42(2), pages 125-134.
    3. Walter, E. & Piet-Lahanier, H. & Happel, J., 1986. "Estimation of non-uniquely identifiable parameters via exhaustive modeling and membership set theory," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 28(6), pages 479-490.
    4. Alejandro F. Villaverde, 2019. "Observability and Structural Identifiability of Nonlinear Biological Systems," Complexity, Hindawi, vol. 2019, pages 1-12, January.

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