<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>This paper develops a simplified Bayesian approach to evaluate a luminescence age. We limit our purpose to the cause-effect relationship between the age and the accumulated dose. The accumulated dose is given as a function of the age and several others parameters: internal radionuclides contents, gamma dose rate, cosmic dose rate, alpha efficiency, wetness, conversion factors, wetness coefficients, fading rate and storage time. The age is the quantity we are looking for. Bayes’ theorem expresses the changes on the probability distribution of age due to the luminescence study. The information before study (prior) comprises what is previously known about the age and the archaeological model (cultural period, stratigraphic relations, type, etc.) as well as the parameters of the physical model. The accumulated dose consists in the data describing the measurement. The various stages of Bayesian approach were implemented using the software WinBugs. Simulated data sets were used in various models. We present various small models representing typical examples encountered in luminescence dating.</p></abstract>

This paper develops a simplified Bayesian approach to evaluate a luminescence age. We limit our purpose to the cause-effect relationship between the age and the accumulated dose. The accumulated dose is given as a function of the age and several others parameters: internal radionuclides contents, gamma dose rate, cosmic dose rate, alpha efficiency, wetness, conversion factors, wetness coefficients, fading rate and storage time. The age is the quantity we are looking for. Bayes’ theorem expresses the changes on the probability distribution of age due to the luminescence study. The information before study (prior) comprises what is previously known about the age and the archaeological model (cultural period, stratigraphic relations, type, etc.) as well as the parameters of the physical model. The accumulated dose consists in the data describing the measurement. The various stages of Bayesian approach were implemented using the software WinBugs. Simulated data sets were used in various models. We present various small models representing typical examples encountered in luminescence dating.

A coarse Bayesian approach to evaluate luminescence ages

Centre de Recherche et de Restauration des Musées de France, Ministère de la Culture, CNRS, Palais du Louvre, Porte des lions, 14 quai F. Mitterrand, 75001, Paris, France

Geochronometria

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"A coarse Bayesian approach to evaluate luminescence ages"}

This paper develops a simplified Bayesian approach to evaluate a luminescence age. We limit our purpose to the cause-effect relationship between the age and...

A coarse Bayesian approach to evaluate luminescence ages

Published Online: Mar 16, 2013

Page range: 90 - 100

DOI: https://doi.org/10.2478/s13386-013-0105-x

Keywords
Luminescence dating, Bayesian statistics, age equation

© 2013 Silesian University of Technology, Gliwice, Poland

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A coarse Bayesian approach to evaluate luminescence ages

Published Online: Mar 16, 2013

Page range: 90 - 100

DOI: https://doi.org/10.2478/s13386-013-0105-x

KeywordsLuminescence dating, Bayesian statistics, age equation

© 2013 Silesian University of Technology, Gliwice, Poland

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
Luminescence dating, Bayesian statistics, age equation