Bayesian nonparametric estimation of the radiocarbon calibration curve
Bayesian nonparametric estimation of the radiocarbon calibration curve
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放射性碳校准曲线的贝叶斯非参数估计
DOI：
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发表时间：
2006
期刊：
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通讯作者：
A. O’Hagan
中科院分区：
文献类型：
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作者：
C. Buck;Delil Gómez Portugal Aguilar;C. Litton;A. O’Hagan
将放射性碳测定校准到校准刻度的过程包括，作为第一阶段，从一组可用的高精度校准数据估计日历和放射性碳年龄之间的关系（放射性碳校准曲线）。传统上，放射性碳校准曲线是通过形成数据的加权平均值，然后将曲线作为连接所得校准数据点的分段线性函数来构建的。用于从平均数据创建校准曲线的替代建议涉及样条或三次插值，或使用傅立叶变换和其他滤波技术，以便获得平滑的校准曲线。在各种方法之间，对于如何利用数据来解决与放射性碳测定校准有关的问题没有达成共识。我们提出了一个非参数贝叶斯解决方案的问题的放射性碳校准曲线的估计，基于高斯过程先验结构的空间上的可能的功能。我们的方法是基于模型的，考虑了测年方法的具体特征，并为估计年代学构建的校准曲线问题提供了通用解决方案。我们将我们的方法应用于1998年国际高精度校准数据集，并证明我们的模型预测校准良好，比其他方法的方差更小。这些数据具有决定性和复杂性，只有在2005年初公布新数据时才能解开，但这种分析表明，非参数贝叶斯模型将允许更精确地校准考古标本的放射性碳年龄。
The process of calibrating radiocarbon determinations onto the cal- endar scale involves, as a rst stage, the estimation of the relationship between calendar and radiocarbon ages (the radiocarbon calibration curve) from a set of available high-precision calibration data. Traditionally the radiocarbon calibra- tion curve has been constructed by forming a weighted average of the data, and then taking the curve as the piece-wise linear function joining the resulting cal- ibration data points. Alternative proposals for creating a calibration curve from the averaged data involve a spline or cubic interpolation, or the use of Fourier transformation and other ltering techniques, in order to obtain a smooth calibra- tion curve. Between the various approaches, there is no consensus as to how to make use of the data in order to solve the problems related to the calibration of radiocarbon determinations. We propose a nonparametric Bayesian solution to the problem of the estimation of the radiocarbon calibration curve, based on a Gaussian process prior structure on the space of possible functions. Our approach is model-based, taking into ac- count specic characteristics of the dating method, and provides a generic solution to the problem of estimating calibration curves for chronology building. We apply our method to the 1998 international high-precision calibration dataset, and demonstrate that our model predictions are well calibrated and have smaller variances than other methods. These data have deciencies and complications that will only be unravelled with the publication of new data, expected in early 2005, but this analysis suggests that the nonparametric Bayesian model will allow more precise calibration of radiocarbon ages for archaeological specimens.