Bayesian statistics applied to Archaeology
Bayesian Modeling of Archaeological Chronologies
ArchaeoPhases: Bayesian Modeling of Archaeological Chronologies
The package ArchaeoPhases provides a list of functions for the statistical analysis and the post-processing of the Markov Chains simulated for instance by Bcal, ChronModel and Oxcal :
– Age Depth curve
– Building a chronology by intervals [phasing]
– Testing the presence of hiatus
– Estimation of a transition between two phases.
– Tempo plot
References
– Philippe A, Vibet M (2020). “Analysis of Archaeological Phases Using the R Package ArchaeoPhases.” Journal of Statistical Software, Code Snippets, 93(1). doi:10.18637/jss.v093.c01 https://doi.org/10.18637/jss.v093.c01.
– Philippe A, Vibet M, Dye T, Frerebeau N (2023). ArchaeoPhases: Post-Processing of Markov Chain Monte Carlo Simulations for Chronological Modelling. Université de Nantes, Nantes, France. R package version 2.0, https://ArchaeoStat.github.io/ArchaeoPhases/.
BayLum : Chronological Bayesian Models Integrating Optically Stimulated Luminescence and Radiocarbon Age Dating.
This includes, among others, data import, export, application of age models and palaeodose model (see Combes, B. & Philippe, A. (2017) and Combes et al (2015))
https://cran.r-project.org/web/packages/BayLum/index.html
Other papers on this topic :
Philippe, Anne, Guillaume Guérin, and Sebastian Kreutzer. 2019. “BayLum - an R Package for Bayesian Analysis of Osl Ages: An Introduction.” Quaternary Geochronology 49: 16-24,. https://doi.org/10.1016/j.quageo.2018.05.009
Guérin, G, C. Lahaye, M. Heydari, M. Autzen, J.-P. Buylaert, P. Guibert, et al. 2020. “Modelling systematic and random errors in OSL dating using the R BayLum package.” https://doi.org/10.5194/gchron-2020-40.