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Journal Articles Communications for Statistical Applications and Methods Year : 2018

Event date model: a robust Bayesian tool for chronology building

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Abstract

We propose a robust event date model to estimate the date of a target event by a combination of individual dates obtained from archaeological artifacts assumed to be contemporaneous. These dates are affected by errors of different types: laboratory and calibration curve errors, irreducible errors related to contaminations, and tapho-nomic disturbances, hence the possible presence of outliers. Modeling based on a hierarchical Bayesian statistical approach provides a simple way to automatically penalize outlying data without having to remove them from the dataset. Prior information on individual irreducible errors is introduced using a uniform shrinkage density with minimal assumptions about Bayesian parameters. We show that the event date model is more robust than models implemented in BCal or OxCal, although it generally yields less precise credibility intervals. The model is extended in the case of stratigraphic sequences that involve several events with temporal order constraints (relative dating), or with duration, hiatus constraints. Calculations are based on Markov chain Monte Carlo (MCMC) numerical techniques and can be performed using ChronoModel software which is freeware, open source and cross-platform. Features of the software are presented in Vibet et al. (ChronoModel v1.5 user's manual, 2016). We finally compare our prior on event dates implemented in the ChronoModel with the prior in BCal and OxCal which involves supplementary parameters defined as boundaries to phases or sequences.
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Dates and versions

insu-01769448 , version 1 (18-04-2018)

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Philippe Lanos, Anne Philippe. Event date model: a robust Bayesian tool for chronology building. Communications for Statistical Applications and Methods, 2018, 25 (2), pp.131-157. ⟨10.29220/CSAM.2018.25.2.131⟩. ⟨insu-01769448⟩
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