Bayesian analysis of radiocarbon dates
If radiocarbon measurements are to be used at all for chronological purposes, we have to use statistical methods for calibration. The most widely used method of calibration can be seen as a simple application of Bayesian statistics, which uses both the information from the new measurement and inform...
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| Format: | Journal article |
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University of Arizona
2009
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| _version_ | 1826293711101755392 |
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| author | Bronk Ramsey, C |
| author_facet | Bronk Ramsey, C |
| author_sort | Bronk Ramsey, C |
| collection | OXFORD |
| description | If radiocarbon measurements are to be used at all for chronological purposes, we have to use statistical methods for calibration. The most widely used method of calibration can be seen as a simple application of Bayesian statistics, which uses both the information from the new measurement and information from the 14C calibration curve. In most dating applications, however, we have larger numbers of 14C measurements and we wish to relate those to events in the past. Bayesian statistics provides a coherent framework in which such analysis can be performed and is becoming a core element in many 14C dating projects. This article gives an overview of the main model components used in chronological analysis, their mathematical formulation, and examples of how such analyses can be performed using the latest version of the OxCal software (v4). Many such models can be put together, in a modular fashion, from simple elements, with defined constraints and groupings. In other cases, the commonly used "uniform phase" models might not be appropriate, and ramped, exponential, or normal distributions of events might be more useful. When considering analyses of these kinds, it is useful to be able run simulations on synthetic data. Methods for performing such tests are discussed here along with other methods of diagnosing possible problems with statistical models of this kind. |
| first_indexed | 2024-03-07T03:34:22Z |
| format | Journal article |
| id | oxford-uuid:bbcb620d-af5c-479c-97e3-9d0c6bdb6e48 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T03:34:22Z |
| publishDate | 2009 |
| publisher | University of Arizona |
| record_format | dspace |
| spelling | oxford-uuid:bbcb620d-af5c-479c-97e3-9d0c6bdb6e482022-03-27T05:19:33ZBayesian analysis of radiocarbon datesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:bbcb620d-af5c-479c-97e3-9d0c6bdb6e48Social Sciences Division - DaisyUniversity of Arizona2009Bronk Ramsey, CIf radiocarbon measurements are to be used at all for chronological purposes, we have to use statistical methods for calibration. The most widely used method of calibration can be seen as a simple application of Bayesian statistics, which uses both the information from the new measurement and information from the 14C calibration curve. In most dating applications, however, we have larger numbers of 14C measurements and we wish to relate those to events in the past. Bayesian statistics provides a coherent framework in which such analysis can be performed and is becoming a core element in many 14C dating projects. This article gives an overview of the main model components used in chronological analysis, their mathematical formulation, and examples of how such analyses can be performed using the latest version of the OxCal software (v4). Many such models can be put together, in a modular fashion, from simple elements, with defined constraints and groupings. In other cases, the commonly used "uniform phase" models might not be appropriate, and ramped, exponential, or normal distributions of events might be more useful. When considering analyses of these kinds, it is useful to be able run simulations on synthetic data. Methods for performing such tests are discussed here along with other methods of diagnosing possible problems with statistical models of this kind. |
| spellingShingle | Bronk Ramsey, C Bayesian analysis of radiocarbon dates |
| title | Bayesian analysis of radiocarbon dates |
| title_full | Bayesian analysis of radiocarbon dates |
| title_fullStr | Bayesian analysis of radiocarbon dates |
| title_full_unstemmed | Bayesian analysis of radiocarbon dates |
| title_short | Bayesian analysis of radiocarbon dates |
| title_sort | bayesian analysis of radiocarbon dates |
| work_keys_str_mv | AT bronkramseyc bayesiananalysisofradiocarbondates |