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Diagnostics for assessing the linear noise and moment closure approximations

Lookup NU author(s): Dr Colin Gillespie, Dr Andrew Golightly

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This is the final published version of an article that has been published in its final definitive form by Walter de Gruyter GmbH, 2016.

For re-use rights please refer to the publisher's terms and conditions.


Abstract

Solving the chemical master equation exactly is typically not possible, so instead we must rely on simulation based methods. Unfortunately, drawing exact realisations, results in simulating every reaction that occurs. This will preclude the use of exact simulators for models of any realistic size and so approximate algorithms become important. In this paper we describe a general framework for assessing the accuracy of the linear noise and two moment approximations. By constructing an efficient space filling design over the parameter region of interest, we present a number of useful diagnostic tools that aids modellers in assessing whether the approximation is suitable. In particular, we leverage the normality assumption of the linear noise and moment closure approximations.


Publication metadata

Author(s): Gillespie CS, Golightly A

Publication type: Article

Publication status: Published

Journal: Statistical Applications in Genetics and Molecular Biology

Year: 2016

Volume: 15

Issue: 5

Pages: 363–379

Print publication date: 01/10/2016

Online publication date: 28/09/2016

Acceptance date: 30/08/2016

Date deposited: 30/08/2016

ISSN (print): 2194-6302

ISSN (electronic): 1544-6115

Publisher: Walter de Gruyter GmbH

URL: http://dx.doi.org/10.1515/sagmb-2014-0071

DOI: 10.1515/sagmb-2014-0071


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