Bayesian Probabilistic Numerical Methods in Time-Dependent State Estimation for Industrial Hydrocyclone Equipment

Oates, CJ, Cockayne, J, Aykroyd, RG orcid.org/0000-0003-3700-0816 et al. (1 more author) (2019) Bayesian Probabilistic Numerical Methods in Time-Dependent State Estimation for Industrial Hydrocyclone Equipment. Journal of the American Statistical Association, 114 (528). pp. 1518-1531. ISSN 0162-1459

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Copyright, Publisher and Additional Information: © 2019 American Statistical Association. This is an author produced version of a paper published in Journal of the American Statistical Association. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Electrical tomography, Inverse problems, Partial differential equations, Probabilistic meshless methods, Sequential Monte Carlo
Dates:
  • Published: 2 October 2019
  • Accepted: 2 January 2019
  • Published (online): 22 February 2019
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: 07 Jan 2019 11:42
Last Modified: 22 Feb 2020 01:38
Status: Published
Publisher: Taylor & Francis
Identification Number: https://doi.org/10.1080/01621459.2019.1574583

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