PROGRESS IN GEOGRAPHY ›› 2016, Vol. 35 ›› Issue (1): 78-88.doi: 10.18306/dlkxjz.2016.01.009

• Orginal Article • Previous Articles     Next Articles

Application of slice sampling method for optimizing OSL age models used for equivalent dose determination

Jun PENG1(), Zhibao DONG1, Fengqing HAN2   

  1. 1. Cold and Arid Regions Environmental and Engineering Research Institute, CAS, Lanzhou 730000, China
    2. Qinghai Institute of Salt Lakes, CAS, Xining 810008, China
  • Online:2016-01-31 Published:2016-01-31
  • Supported by:
    National Basic ResearchProgram of China (973 Program), No.2013CB956000, No.2012CB426501


In Optically Stimulated Luminescence (OSL) dating, statistical age models used for equivalent dose (De) determination are probabilistic models constructed according to mathematical statistics. They are applied to distinguish De populations that are sedimentologically different or to determine a De value that represents the burial dose of a sample. Maximum likelihood estimation (MLE) method is routinely used to optimize parameters of an age model. In the present study, we used the Slice sampling algorithm to determine the parameters of age models. Slice sampling is a Markov chain Monte Carlo (MCMC) sampling method, which enables the sampling distributions of parameters to be obtained from the joint likelihood function that is determined by observations and the specified model. This study applied easily implemented and openly accessible numeric routines to performing the algorithm. We used artificial and measured datasets to check the reliability of the estimates. MCMC method is insensitive to the parameters’ initial states, and the standard errors (or confidence intervals) of parameters assessed using this method are more reliable compared to those based on the Fisher information matrix constructed through numerical differentiation. Our results indicate that the Slice sampling method provides an alternative for age model optimization. Slice sampling method generates an informative estimation for the results of MLE method in age model application.

Key words: OSL dating, equivalent dose, statistical age models, parameter optimization, stochastic sampling