INFERENCE FROM LARGE SETS OF RADIOCARBON DATES: SOFTWARE AND METHODS
2020/10/06 by Enrico R. Crema, Enrico R Crema, Andrew Bevan · 300 citations
Earth and Planetary Sciences · Engineering · Environmental Science · Mathematics · #Archaeology #Archaeology and ancient environmental studies #Artificial intelligence #Computer science #Engineering #Geography #Geology and Paleoclimatology Research #Inference #Isotope Analysis in Ecology #Mathematics #Monte Carlo method #Permutation (music) #Population #Programming language #Radiocarbon dating #Range (aeronautics) #Software #Statistical inference #Statistics
paper · pdf · doi:10.1017/rdc.2020.95
published in Radiocarbon 63(1), 23-39 (Cambridge University Press)
openalex publication_date 2020/10/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
Abstract
ABSTRACT The last decade has seen the development of a range of new statistical and computational techniques for analysing large collections of radiocarbon ( 14 C) dates, often but not exclusively to make inferences about human population change in the past. Here we introduce rcarbon , an open-source software package for the R statistical computing language which implements many of these techniques and looks to foster transparent future study of their strengths and weaknesses. In this paper, we review the key assumptions, limitations and potentials behind statistical analyses of summed probability distribution of 14 C dates, including Monte-Carlo simulation-based tests, permutation tests, and spatial analyses. Supplementary material provides a fully reproducible analysis with further details not covered in the main paper.
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