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A New Robust Statistical Model for Radiocarbon Data

Bibliographic Data

ID9245117
AuthorsJ Andrés Christen (0000-0002-5795-4345), Sergio Pérez E
Year2009
Volume51
Issue3
Pages1047-1059
Publication date2009-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueRadiocarbon (JOURNAL)
Journal identifiersISSN: 0033-8222 • E-ISSN: 1945-5755
PublisherCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/s003382220003410x
OpenAlexW2205675661
LanguageEN
Citations received21
References cited14

The general method currently used to analyze radiocarbon data ( y ) is conditional on the standard deviation (σ), reported by 14 C laboratories, which reflects the uncertainty in the dating process. This uncertainty is measured through a series of empirical as well as theoretical considerations about the dating process, chemical preprocessing, etc. Nevertheless, σ is assumed as known in the statistical model for 14 C data used since the dawn of the discipline. This paper proposes a method for the analysis of 14 C data where the associated variance is taken as the product of an unknown constant α with the sum of the variance reported by the laboratory σ 2 and the variance of the calibration curve σ 2 (θ) (that is, an unknown error multiplier). Using this approach, assuming that the 14 C determination y arises from a Normal population and that, a priori, α has an inverse gamma distribution InvGa( a, b ), the resulting dating model is a t distribution with 2 a degrees of freedom. The introduction of parameters a and b allows a robust analysis in the presence of atypical data and at the same time incorporates the uncertainty associated with the intra- and interlaboratory error assessment processes. Comparisons with the common Normal model show that the proposed t model produces smoother posterior distributions and seem to be far more robust to atypical data, presenting a simpler alternative to the standard 14 C outlier analysis. Moreover, this new model might be a step forward in understanding and explaining the otherwise elusive scatter in 14 C data seen in interlaboratory studies

A priori and a posteriori · Calibration · Econometrics · Outlier · Population · Standard deviation · Statistics · Archaeology and ancient environmental studies · Cultural Heritage Materials Analysis · Image Processing and 3D Reconstruction · Mathematics

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Unique citing works21
Citations per year1.4
Citation span2011 - 2026 (16)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 18

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