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

download R CRAN

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.