If you want to examine the analysis directly, the paper links the algorithm as part of the Baydem R package [0] and the R dataset used is available in its own repository [1] (docker recommended):
Commenting mostly to save, but also, I (rank amateur, not to be taken seriously) spent some time looking at radiocarbon dating and was alarmed at the inconstancy of, and sensitivity to, calibration curves in the analysis. My intuition was that this had to do with the linear calibration problem, but this paper has taken a wholly different approach. I look forward to spending more time with the paper and playing with the R library.
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[ 3.5 ms ] story [ 28.5 ms ] thread[0]: https://github.com/eehh-stanford/baydem/
[1]: https://github.com/MichaelHoltonPrice/price_et_al_tikal_rc
Commenting mostly to save, but also, I (rank amateur, not to be taken seriously) spent some time looking at radiocarbon dating and was alarmed at the inconstancy of, and sensitivity to, calibration curves in the analysis. My intuition was that this had to do with the linear calibration problem, but this paper has taken a wholly different approach. I look forward to spending more time with the paper and playing with the R library.
Thanks for sharing!