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    A New Robust Statistical Model for Radiocarbon Data

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    Author
    Christen, J. Andrés
    Pérez E., Sergio
    Issue Date
    2009-01-01
    
    Metadata
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    Citation
    Christen, J. A., & Pérez E., S. (2009). A new robust statistical model for radiocarbon data. Radiocarbon, 51(3), 1047-1059.
    Publisher
    Department of Geosciences, The University of Arizona
    Journal
    Radiocarbon
    URI
    http://hdl.handle.net/10150/654117
    DOI
    10.1017/S003382220003410X
    Additional Links
    http://radiocarbon.webhost.uits.arizona.edu/
    Abstract
    The general method currently used to analyze radiocarbon data (y) is conditional on the standard deviation (), reported by 14C 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, is assumed as known in the statistical model for 14C data used since the dawn of the discipline. This paper proposes a method for the analysis of 14C data where the associated variance is taken as the product of an unknown constant with the sum of the variance reported by the laboratory 2 and the variance of the calibration curve 2() (that is, an unknown error multiplier). Using this approach, assuming that the 14C determination y arises from a Normal population and that, a priori, has an inverse gamma distribution InvGa(a, b), the resulting dating model is a t distribution with 2a 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 14C outlier analysis. Moreover, this new model might be a step forward in understanding and explaining the otherwise elusive scatter in 14C data seen in interlaboratory studies.
    Type
    Article
    text
    Language
    en
    ISSN
    0033-8222
    ae974a485f413a2113503eed53cd6c53
    10.1017/S003382220003410X
    Scopus Count
    Collections
    Radiocarbon, Volume 51, Number 3 (2009)

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