(a) Testing continuous piecewise linear model for a typical sample size
5 and 7.5 kyr BP. We then randomly sample N = 1500 dates under this true (toy) population curve, ‘uncalibrate’ these dates, apply an arbitrary 14 C error of 25 years, then calibrate. We then conduct a parameter search for the best fitting 1-CPL, 2-CPL, 3-CPL, 4-CPL and 5-CPL models. The BIC is calculated using: ln(n) k ? 2 ln(L), where k is the number of parameters (k = 2p ? 1, where p is the number of phases), n is the number of 14 C dates and L is the ML . Table 1 gives the results of this model comparison and shows that the model fits closer to the data as its complexity increases. However, the BIC shows that the model is overfitted beyond a 3-CPL model. Therefore, the model selection process successfully recovered the 3-CPL model from which the data were generated.
Table 1. The 3-CPL model is selected as the best, since it has the lowest BIC (italics). Continue reading “To demonstrate our approach, we first generate a true (toy) population curve, which comprises a 3-CPL model PDF between 5”