Using Bayesian dynamical systems, model averaging and neural networks to determine interactions between socio-economic indicators

Blomqvist, BRH, Mann, RP orcid.org/0000-0003-0701-1274 and Sumpter, DJT (2018) Using Bayesian dynamical systems, model averaging and neural networks to determine interactions between socio-economic indicators. PLoS ONE, 13 (5). e0196355. ISSN 1932-6203

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Copyright, Publisher and Additional Information: © 2018 Blomqvist et al. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Dates:
  • Published: 9 May 2018
  • Accepted: 11 April 2018
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Maths and Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 19 Apr 2018 09:36
Last Modified: 18 May 2018 13:21
Status: Published
Publisher: Public Library of Science
Identification Number: https://doi.org/10.1371/journal.pone.0196355

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