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.

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Autores principales:	Bedartha Goswami, Niklas Boers, Aljoscha Rheinwalt, Norbert Marwan, Jobst Heitzig, Sebastian F. M. Breitenbach, Jürgen Kurths
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/0e3d61b1efc947cfb08752dc628291d8
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spelling	oai:doaj.org-article:0e3d61b1efc947cfb08752dc628291d82021-12-02T17:33:16ZAbrupt transitions in time series with uncertainties10.1038/s41467-017-02456-62041-1723https://doaj.org/article/0e3d61b1efc947cfb08752dc628291d82018-01-01T00:00:00Zhttps://doi.org/10.1038/s41467-017-02456-6https://doaj.org/toc/2041-1723Most 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.Bedartha GoswamiNiklas BoersAljoscha RheinwaltNorbert MarwanJobst HeitzigSebastian F. M. BreitenbachJürgen KurthsNature PortfolioarticleScienceQENNature Communications, Vol 9, Iss 1, Pp 1-10 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Bedartha Goswami Niklas Boers Aljoscha Rheinwalt Norbert Marwan Jobst Heitzig Sebastian F. M. Breitenbach Jürgen Kurths Abrupt transitions in time series with uncertainties
description	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.
format	article
author	Bedartha Goswami Niklas Boers Aljoscha Rheinwalt Norbert Marwan Jobst Heitzig Sebastian F. M. Breitenbach Jürgen Kurths
author_facet	Bedartha Goswami Niklas Boers Aljoscha Rheinwalt Norbert Marwan Jobst Heitzig Sebastian F. M. Breitenbach Jürgen Kurths
author_sort	Bedartha Goswami
title	Abrupt transitions in time series with uncertainties
title_short	Abrupt transitions in time series with uncertainties
title_full	Abrupt transitions in time series with uncertainties
title_fullStr	Abrupt transitions in time series with uncertainties
title_full_unstemmed	Abrupt transitions in time series with uncertainties
title_sort	abrupt transitions in time series with uncertainties
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/0e3d61b1efc947cfb08752dc628291d8
work_keys_str_mv	AT bedarthagoswami abrupttransitionsintimeserieswithuncertainties AT niklasboers abrupttransitionsintimeserieswithuncertainties AT aljoscharheinwalt abrupttransitionsintimeserieswithuncertainties AT norbertmarwan abrupttransitionsintimeserieswithuncertainties AT jobstheitzig abrupttransitionsintimeserieswithuncertainties AT sebastianfmbreitenbach abrupttransitionsintimeserieswithuncertainties AT jurgenkurths abrupttransitionsintimeserieswithuncertainties
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Abrupt transitions in time series with uncertainties

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