Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-22T04:14:46.607Z Has data issue: false hasContentIssue false
  • English
  • Français

MCMC for a hyperbolic Bayesian inverse problem in traffic flow modelling – ADDENDUM

Published online by Cambridge University Press:  04 April 2022

Jeremie Coullon  and
Yvo Pokern

Abstract

An abstract is not available for this content. As you have access to this content, full HTML content is provided on this page. A PDF of this content is also available in through the ‘Save PDF’ action button.
Type
Addendum
Information
Data-Centric Engineering , Volume 3 , 2022 , e8
Check for updates
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press

The editors and publisher of Data-Centric Engineering have awarded the Open Data and Open Materials badges to this article Coullon, J., & Pokern, Y. (2022).

Open Data Badge—indicates that data necessary to reproduce the reported results is available in an open access repository, under an open licence, with an accompanying description of the data.

Open Materials Badge—indicates that any infrastructure, instruments, or equipment related to the reported methodology are available in an open access repository and are described in sufficient detail to allow a researcher to reproduce the procedure.

The original article has been updated to include the badges. Please refer to the Data Availability Statement to find the identifier linking to the open data or open materials.

References

Coullon, J., & Pokern, Y. (2022). Markov chain Monte Carlo for a hyperbolic Bayesian inverse problem in traffic flow modeling. Data-Centric Engineering, 3, E4. doi:10.1017/dce.2022.3CrossRefGoogle Scholar
Submit a response

Comments

No Comments have been published for this article.