Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics
NPG
Articles | Volume 23, issue 1
Articles | Volume 23, issue 1
https://doi.org/10.5194/npg-23-31-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/npg-23-31-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Articles | Volume 23, issue 1
Research article
 | 
29 Feb 2016
Research article |  | 29 Feb 2016

A sequential Bayesian approach for the estimation of the age–depth relationship of the Dome Fuji ice core

Shin'ya Nakano, Kazue Suzuki, Kenji Kawamura, Frédéric Parrenin, and Tomoyuki Higuchi

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Short summary
This paper proposes a technique for dating an ice core. The proposed technique employs a hybrid method combining the sequential Monte Carlo method and the Markov chain Monte Carlo method, which is referred to as the particle Markov chain Monte Carlo method. The sequential Monte Carlo method, which is also known as the particle filter, is widely used for nonlinear time-series analysis. This paper demonstrates the usefulness of the approach in time-series analysis for dating an ice core.
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