Abrupt transitions in time series with uncertainties
Most time series techniques tend to ignore data uncertainties, which results in inaccurate conclusions. Here, Goswami et al. represent time series as a sequence of probability density functions, and reliably detect abrupt transitions by identifying communities in probabilistic recurrence networks.
Guardado en:
Autores principales: | Bedartha Goswami, Niklas Boers, Aljoscha Rheinwalt, Norbert Marwan, Jobst Heitzig, Sebastian F. M. Breitenbach, Jürgen Kurths |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2018
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Materias: | |
Acceso en línea: | https://doaj.org/article/0e3d61b1efc947cfb08752dc628291d8 |
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