Detection of outliers with a Bayesian hierarchical model: application to the single-grain luminescence dating method. - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Electronic Journal of Applied Statistical Analysis Année : 2021

Detection of outliers with a Bayesian hierarchical model: application to the single-grain luminescence dating method.

Résumé

The event model was proposed by Lanos and Philippe (2018) to combine measurements in the context of archaeological chronological dating. We extend this model to luminescence dating and define a new strategy to detect outliers from the hyperparameters of the event model. This procedure is applied to the combination of Gaussian measurements and luminescence age estimation. We illustrate through simulations that it is preferable, in terms of accuracy and precision, to exclude detected outliers rather than use the robust estimation method (e.g. the event model).
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Dates et versions

hal-04322635 , version 1 (05-12-2023)

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Jean-Michel Galharret, Anne Philippe, Norbert Mercier. Detection of outliers with a Bayesian hierarchical model: application to the single-grain luminescence dating method.. Electronic Journal of Applied Statistical Analysis, 2021, ⟨10.1285/i20705948v14n2p318⟩. ⟨hal-04322635⟩
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