In optically stimulated luminescence (OSL) dating, statistical age models for equivalent dose (D_e) distributions are routinely estimated using the maximum likelihood estimation (MLE) method. In this study, a Markov chain Monte Carlo (MCMC) method was used to analyze statistical age models, including the central age model (CAM), the minimum age model (MAM), the maximum age model (MXAM), etc. This method was first used to obtain sampling distributions on parameters of interest in an age model using D_e distributions from individual sedimentary samples and subsequently extended to simultaneously extract age estimates from multiple samples with stratigraphic constraints. The MCMC method allows for the use of Bayesian inference to refine chronological sequences from multiple samples, including both fully and partially bleached OSL dates. This study designed easily implemented open-source numeric programs to perform MCMC sampling. Measured and simulated D_e distributions are used to validate the reliability of dose (age) estimates obtained by this method. Findings from this study demonstrate that estimates obtained by the MCMC method can be used to informatively compare results obtained by the MLE method. The application of statistical age models to multiple OSL dates with stratigraphic orders using the MCMC method may significantly improve both the precision and accuracy of burial ages.

中文翻译：

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使用马尔可夫链蒙特卡洛方法分析统计年龄模型以确定等效剂量和埋葬年龄

在光学激发发光（OSL）测年中，通常使用最大似然估计（MLE）方法估计等效剂量（D _e）分布的统计年龄模型。在这项研究中，使用马尔可夫链蒙特卡罗（MCMC）方法来分析统计年龄模型，包括中央年龄模型（CAM），最小年龄模型（MAM），最大年龄模型（MXAM）等。该方法首先用于使用D _e获得年龄模型中感兴趣参数的采样分布。单个沉积物样本的分布，随后扩展为同时从具有地层限制的多个样本中提取年龄估计。MCMC方法允许使用贝叶斯推理来从多个样本（包括完全和部分漂白的OSL日期）中细化时间顺序。这项研究设计了易于实施的开源数字程序来执行MCMC采样。测量和模拟的D _e分布用于验证通过此方法获得的剂量（年龄）估计值的可靠性。这项研究的结果表明，通过MCMC方法获得的估计值可用于在信息上比较通过MLE方法获得的结果。使用MCMC方法将统计年龄模型应用于具有地层顺序的多个OSL日期可能会显着提高埋葬年龄的准确性和准确性。