A Hybrid Symbolic-Numerical Method for Determining Model Structure

Choquet, R. and Cole, Diana J. (2012) A Hybrid Symbolic-Numerical Method for Determining Model Structure. Mathematical Biosciences, 236 (2). pp. 117-125. ISSN 0025-5564. (The full text of this publication is not available from this repository)

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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
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science
Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Diana Cole
Date Deposited: 30 Mar 2012 08:38
Last Modified: 30 Apr 2014 10:11
Resource URI: http://kar.kent.ac.uk/id/eprint/29235 (The current URI for this page, for reference purposes)
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