New Methods and Critical Aspects in Bayesian Mathematics for 14 C Calibration

Datos Bibliográficos

ID9244142
AutoresPeter Steier (0000-0002-6144-2449), Werner Rom, Stephan Puchegger
Año2001
Volumen43
Número2A
Páginas373-380
Fecha de publicación2001-01-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaRadiocarbon (JOURNAL)
Identificadores de la revistaISSN: 0033-8222 • E-ISSN: 1945-5755
EditorialCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/s0033822200038236
OpenAlexW2476332325
IdiomaEN
Citas recibidas14
Referencias citadas9

The probabilistic radiocarbon calibration approach, which largely has replaced the intercept method in 14 C dating, is based on the so-called Bayes' theorem (Bayes 1763). Besides single-sample calibration, Bayesian mathematics also supplies tools for combining 14 C results of many samples with independent archaeological information such as typology or stratigraphy (Buck et al. 1996). However, specific assumptions in the “prior probabilities”, used to transform the archaeological information into mathematical probability distributions, may bias the results (Steier and Rom 2000). A general technique for guarding against such a bias is “sensitivity analysis”, in which a range of possible prior probabilities is tested. Only results that prove robust in this analysis should be used. We demonstrate the impact of this method for an assumed, yet realistic case of stratigraphically ordered samples from the Hallstatt period, i.e. the Early Iron Age in Central Europe

Archaeology · Bayes' theorem · Bayesian probability · Calibration · Chromatography · Geography · Prior information · Prior probability · Probabilistic logic · Radiocarbon dating · Statistics · Typology · Archaeology and ancient environmental studies · Chemistry · Computer Science · Engineering · Geology and Paleoclimatology Research · Image Processing and 3D Reconstruction · Mathematics · Artificial Intelligence · Geology · Paleontology · Stratigraphy