Oil Commodity Movement Estimation: Analysis with Gaussian Process and Data Science
In this study, Gaussian process (GP) regression is used to normalize observed commodity data and produce predictions at densely interpolated time intervals. The methodology is applied to an empirical oil price dataset. A Gaussian kernel with data-dependent initialization is used to calculate predict...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Commodities |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2813-2432/4/2/9 |
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