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  Bayesian regression versus machine learning for rapid age estimation of archaeological features identified with lidar at Angkor

Carleton, W. C., Klassen, S., Niles-Weed, J., Evans, D., Roberts, P., & Groucutt, H. S. (2023). Bayesian regression versus machine learning for rapid age estimation of archaeological features identified with lidar at Angkor. Scientific Reports, 13: 17913. doi:10.1038/s41598-023-44875-0.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-F934-0 Version Permalink: https://hdl.handle.net/21.11116/0000-000D-F935-F
Genre: Journal Article

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https://doi.org/10.1038/s41598-023-44875-0 (Publisher version)
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 Creators:
Carleton, W. Christopher, Author
Klassen, Sarah, Author
Niles-Weed, Jonathan, Author
Evans, Damian, Author
Roberts, Patrick, Author
Groucutt, Huw S.1, Author           
Affiliations:
1Max Planck Research Group Extreme Events, Dr. Huw Groucutt, MPI for Chemical Ecology, Max Planck Society, ou_3018879              

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 Dates: 2023-10-122023-10-20
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: Introduction
Results
Discussion
Methods
- Temple data
- Hybrid GLM‑GSSL approach
- Bayesian approach
- Model comparison
- Variable importance
- Visualizing chronological uncertainty
- Software
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41598-023-44875-0
Other: HUW047
 Degree: -

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Title: Scientific Reports
  Abbreviation : Sci. Rep.
Source Genre: Journal
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Publ. Info: London, UK : Nature Publishing Group
Pages: - Volume / Issue: 13 Sequence Number: 17913 Start / End Page: - Identifier: ISSN: 2045-2322
CoNE: https://pure.mpg.de/cone/journals/resource/2045-2322