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A Hybrid Symbolic-Numerical Method for Determining Model Structure

Choquet, R., Cole, Diana J. (2012) A Hybrid Symbolic-Numerical Method for Determining Model Structure. Mathematical Biosciences, 236 (2). pp. 117-125. ISSN 0025-5564. (doi:10.1016/j.mbs.2012.02.002) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:29235)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1016/j.mbs.2012.02.002

Abstract

In this article, we present a method for determining whether a model is at least locally identifiable and in the case of non-identifiable models whether any of the parameters are individually at least locally identifiable. This method combines symbolic and numeric methods to create an algorithm that is extremely accurate compared to other numeric methods and computationally inexpensive. A series of generic computational steps are developed to create a method that is ideal for practitioners to use. The algorithm is compared to symbolic methods for two capture-recapture models and a compartment model.

Item Type: Article
DOI/Identification number: 10.1016/j.mbs.2012.02.002
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Diana Cole
Date Deposited: 30 Mar 2012 08:38 UTC
Last Modified: 16 Nov 2021 10:07 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/29235 (The current URI for this page, for reference purposes)

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