<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>The optically stimulated luminescence (OSL) decay curve is assumed to consist of a number of first-order exponential components. Improper estimation of the number of components leads to under-or over-fitting of the curve under consideration. Hence, correct estimation of the number of components is important to accurately analyze an OSL decay curve. In this study, we investigated the possibility of using the Bayesian Information Criterion to estimate the optimal number of components in an OSL decay curve. We tested the reliability of this method using several hundred measured decay curves and three simulation scenarios. Our results demonstrate that the quality of the identification can be influenced by several factors: the measurement time and the number of channels; the variability of the decay constants; and the signal-to-noise ratios of a decaying component. The results also suggest that the Bayesian Information Criterion has great potential to estimate the number of components in an OSL decay curve with a moderate to high signal-to-noise ratio.</p></abstract>

The optically stimulated luminescence (OSL) decay curve is assumed to consist of a number of first-order exponential components. Improper estimation of the number of components leads to under-or over-fitting of the curve under consideration. Hence, correct estimation of the number of components is important to accurately analyze an OSL decay curve. In this study, we investigated the possibility of using the Bayesian Information Criterion to estimate the optimal number of components in an OSL decay curve. We tested the reliability of this method using several hundred measured decay curves and three simulation scenarios. Our results demonstrate that the quality of the identification can be influenced by several factors: the measurement time and the number of channels; the variability of the decay constants; and the signal-to-noise ratios of a decaying component. The results also suggest that the Bayesian Information Criterion has great potential to estimate the number of components in an OSL decay curve with a moderate to high signal-to-noise ratio.

Estimating the number of components in an OSL decay curve using the Bayesian Information Criterion

Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, 730000, China

Qinghai Institute of Salt Lakes, Chinese Academy of Sciences, Xining, 810008, China

Lanzhou Center for Oil and Gas Resources, Institute of Geology and Geophysics, CAS, Lanzhou, 730000, China

Geochronometria

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

The optically stimulated luminescence (OSL) decay curve is assumed to consist of a number of first-order exponential components. Improper estimation of the...

Estimating the number of components in an OSL decay curve using the Bayesian Information Criterion

Published Online: Oct 01, 2014

Page range: 334 - 341

DOI: https://doi.org/10.2478/s13386-013-0166-x

Keywords
OSL decay curves, number of components, Bayesian Information Criterion

© 2013 Silesian University of Technology, Gliwice, Poland

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

Estimating the number of components in an OSL decay curve using the Bayesian Information Criterion

Published Online: Oct 01, 2014

Page range: 334 - 341

DOI: https://doi.org/10.2478/s13386-013-0166-x

KeywordsOSL decay curves, number of components, Bayesian Information Criterion

© 2013 Silesian University of Technology, Gliwice, Poland

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

Keywords
OSL decay curves, number of components, Bayesian Information Criterion