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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2408.08806 |
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| _version_ | 1866916733698179072 |
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| author | McLatchie, Yann Fong, Edwin Frazier, David T. Knoblauch, Jeremias |
| author_facet | McLatchie, Yann Fong, Edwin Frazier, David T. Knoblauch, Jeremias |
| contents | We analyse the impact of using tempered likelihoods in the production of posterior predictions. While the choice of temperature has an impact on predictive performance in small samples, we formally show that in moderate-to-large samples, tempering does not impact posterior predictions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_08806 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Predictive performance of power posteriors McLatchie, Yann Fong, Edwin Frazier, David T. Knoblauch, Jeremias Statistics Theory We analyse the impact of using tempered likelihoods in the production of posterior predictions. While the choice of temperature has an impact on predictive performance in small samples, we formally show that in moderate-to-large samples, tempering does not impact posterior predictions. |
| title | Predictive performance of power posteriors |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2408.08806 |