Reconstructing prehistoric human demography using end-to-end Bayesian analysis of radiocarbon dates

Presently, summed probability densities (SPDs) of calibrated radiocarbon dates are the dominant method of summarizing sets of radiocarbon dates (e.g., to reconstruct demographic trends). Unfortunately, SPDs are incapable of converging on their true generating distributions even as the number of observations gets large. Michael Price describes an alternative, end-to-end Bayesian approach and show via simulations and a statistical identifiability analysis that the end-to-end approach correctly converges on the generating distribution.