Bayesian model selection for the glacial-interglacial cycle
A prevailing viewpoint in paleoclimate science is that a single paleoclimate record contains insufficient information to discriminate between typical competing explanatory models. Here we show that by using SMC 2 (sequential Monte Carlo squared) combined with novel Brownian bridge type proposals for...
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| Format: | Article |
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Wiley
2017
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| Online Access: | https://eprints.nottingham.ac.uk/41271/ |
| _version_ | 1848796235888066560 |
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| author | Carson, Jake Crucifix, Michel Preston, Simon Wilkinson, Richard |
| author_facet | Carson, Jake Crucifix, Michel Preston, Simon Wilkinson, Richard |
| author_sort | Carson, Jake |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | A prevailing viewpoint in paleoclimate science is that a single paleoclimate record contains insufficient information to discriminate between typical competing explanatory models. Here we show that by using SMC 2 (sequential Monte Carlo squared) combined with novel Brownian bridge type proposals for the state trajectories, it is possible to estimate Bayes factors to sufficient accuracy to be able to select between competing models, even with relatively short time series. The results show that Monte Carlo methodology and computer power have now advanced to the point where a full Bayesian analysis for a wide class of conceptual climate models is now possible. The results also highlight a problem with estimating the chronology of the climate record prior to further statistical analysis, a practice which is common in paleoclimate science. Using two datasets based on the same record but with different estimated chronologies, results in conflicting conclusions about the importance of the astronomical forcing on the glacial cycle, and about the internal dynamics generating the glacial cycle, even though the difference between the two estimated chronologies is consistent with dating uncertainty. This highlights a need for chronology estimation and other inferential questions to be addressed in a joint statistical
procedure. |
| first_indexed | 2025-11-14T19:44:46Z |
| format | Article |
| id | nottingham-41271 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:44:46Z |
| publishDate | 2017 |
| publisher | Wiley |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-412712020-05-04T19:23:46Z https://eprints.nottingham.ac.uk/41271/ Bayesian model selection for the glacial-interglacial cycle Carson, Jake Crucifix, Michel Preston, Simon Wilkinson, Richard A prevailing viewpoint in paleoclimate science is that a single paleoclimate record contains insufficient information to discriminate between typical competing explanatory models. Here we show that by using SMC 2 (sequential Monte Carlo squared) combined with novel Brownian bridge type proposals for the state trajectories, it is possible to estimate Bayes factors to sufficient accuracy to be able to select between competing models, even with relatively short time series. The results show that Monte Carlo methodology and computer power have now advanced to the point where a full Bayesian analysis for a wide class of conceptual climate models is now possible. The results also highlight a problem with estimating the chronology of the climate record prior to further statistical analysis, a practice which is common in paleoclimate science. Using two datasets based on the same record but with different estimated chronologies, results in conflicting conclusions about the importance of the astronomical forcing on the glacial cycle, and about the internal dynamics generating the glacial cycle, even though the difference between the two estimated chronologies is consistent with dating uncertainty. This highlights a need for chronology estimation and other inferential questions to be addressed in a joint statistical procedure. Wiley 2017-12-21 Article PeerReviewed Carson, Jake, Crucifix, Michel, Preston, Simon and Wilkinson, Richard (2017) Bayesian model selection for the glacial-interglacial cycle. Journal of the Royal Statistical Society: Series C, 67 (1). pp. 25-54. ISSN 0035-9254 Astronomical forcing; Glacial cycles; Model comparison; Paleoclimate; Sequential Monte Carlo methods http://onlinelibrary.wiley.com/doi/10.1111/rssc.12222/full doi:10.1111/rssc.12222 doi:10.1111/rssc.12222 |
| spellingShingle | Astronomical forcing; Glacial cycles; Model comparison; Paleoclimate; Sequential Monte Carlo methods Carson, Jake Crucifix, Michel Preston, Simon Wilkinson, Richard Bayesian model selection for the glacial-interglacial cycle |
| title | Bayesian model selection for the glacial-interglacial cycle |
| title_full | Bayesian model selection for the glacial-interglacial cycle |
| title_fullStr | Bayesian model selection for the glacial-interglacial cycle |
| title_full_unstemmed | Bayesian model selection for the glacial-interglacial cycle |
| title_short | Bayesian model selection for the glacial-interglacial cycle |
| title_sort | bayesian model selection for the glacial-interglacial cycle |
| topic | Astronomical forcing; Glacial cycles; Model comparison; Paleoclimate; Sequential Monte Carlo methods |
| url | https://eprints.nottingham.ac.uk/41271/ https://eprints.nottingham.ac.uk/41271/ https://eprints.nottingham.ac.uk/41271/ |