On the identifiability and distinguishability of nonlinear parametric models

Eric Walter and Luc Pronzato

Mathematics and Computers in Simulation (MATCOM), 1996, vol. 42, issue 2, 125-134

Abstract: Testing parametric models for identifiability and distinguishability is important when the parameters to be estimated have a physical meaning or when the model is to be used to reconstruct physically meaningful state variables that cannot be measured directly. Examples are used to explain why and indicate briefly how, with special emphasis on nonlinear models.

Date: 1996
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0378475495001239
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:42:y:1996:i:2:p:125-134

DOI: 10.1016/0378-4754(95)00123-9

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().