Estimating temporal likelihood of archaeological sites in prehistoric Denmark combining typochronological and radiocarbon data

The surge in data availability and methodological advancements over the last decades has enabled archaeologists to develop more robust data-driven models, which are essential for reconstructing ancient human history. However, despite their potential, these datasets pose significant challenges due to their heterogeneity and inherent uncertainties. A common limitation is the low chronological resolution of many datasets, which often compels archaeologists to rely on proxies such as radiocarbon date frequency distributions to study variations in occupation intensity. While this approach is widely used, it necessitates a large number of radiocarbon samples to construct probability curves, leading to a considerable loss of spatial resolution. To address these challenges, I propose a novel method that combines typochronological and radiocarbon datasets, preserving both temporal and spatial resolution while accounting for uncertainty. Each relatively dated site is assigned a simulated calendar date within its chronological span, based on the cumulative probability distribution of locally available radiocarbon data. The results are grouped into uniform time windows, with each site assigned a likelihood of belonging to each time period. The efficacy and functionality of the method are demonstrated using toy data, with the results compared to outputs from alternative methods. Finally, the method is applied to four case studies from prehistoric Denmark (4000 − 500 BC), showcasing its potential in addressing long-standing challenges in archaeological modelling. The results show that despite the known global trends, local variation is observed in the four different sub-regions considered.