The effect of COVID-19 on minor dry bulk shipping : a Bayesian time series and a neural networks approach

Molaris, V.A., Triantafyllopoulos, K. orcid.org/0000-0002-4144-4092, Papadakis, G. et al. (2 more authors) (2021) The effect of COVID-19 on minor dry bulk shipping : a Bayesian time series and a neural networks approach. Communications in Statistics: Case Studies, Data Analysis and Applications, 7 (4). pp. 624-638.

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Item Type: Article
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© 2021 Taylor & Francis Group, LLC. This is an author-produced version of a paper subsequently published in Communications in Statistics: Case Studies, Data Analysis and Application. Uploaded in accordance with the publisher's self-archiving policy.

Keywords: Time series analysis; neural networks; dry bulk shipping
Dates:
  • Published: 2 October 2021
  • Published (online): 2 October 2021
  • Accepted: 1 September 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 11 Nov 2021 07:24
Last Modified: 02 Oct 2022 00:13
Status: Published
Publisher: Taylor & Francis
Refereed: Yes
Identification Number: 10.1080/23737484.2021.1979434
Open Archives Initiative ID (OAI ID):

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