A Bayesian Approach to the Estimation of Radiocarbon Calibration Curves: The IntCal09 Methodology

Abstract

This article presents a new approach to the construction of radiocarbon calibration curves. The Bayesian methodology was developed specifically to facilitate construction of the 2009 updates to the internationally agreed ¹⁴C calibration curves known as IntCal09 and Marine09. The curve estimation approach taken uses Markov chain Monte Carlo sampling, specifically a Metropolis-within-Gibbs sampler, which offers improved flexibility and reliability over the approaches used in the past. In particular, the method allows accurate modeling of calibration data with ¹⁴C determinations that arise from material deposited over several consecutive calendar years and that exhibit complex uncertainty structures on their calendar date estimates (arising from methods such as wiggle-matching and varve counting).