Change-Point Detection of Climate Time Series by Nonparametric Method

Abstract—In one of the data mining techniques, change-point detection is of importance in evaluating time series measured in real world. For decades this technique has been developed as a nonlinear dynamics. We apply the method for detecting the change points, Singular Spectrum Transformation (SST),...

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Main Authors: Naoki Itoh, Jürgen Kurths
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
change-point
Arctic
Wrangel Island
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.4237
http://www.iaeng.org/publication/WCECS2010/WCECS2010_pp445-448.pdf
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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.301.4237 2023-05-15T14:58:20+02:00 Change-Point Detection of Climate Time Series by Nonparametric Method Naoki Itoh Jürgen Kurths The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.4237 http://www.iaeng.org/publication/WCECS2010/WCECS2010_pp445-448.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.4237 http://www.iaeng.org/publication/WCECS2010/WCECS2010_pp445-448.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.iaeng.org/publication/WCECS2010/WCECS2010_pp445-448.pdf change-point text ftciteseerx 2016-01-07T22:05:40Z Abstract—In one of the data mining techniques, change-point detection is of importance in evaluating time series measured in real world. For decades this technique has been developed as a nonlinear dynamics. We apply the method for detecting the change points, Singular Spectrum Transformation (SST), to the climate time series. To know where the structures of climate data sets change can reveal a climate background. In this paper we discuss the structures of precipitation data in Kenya and Wrangel Island (Arctic land) by using the SST. Text Arctic Wrangel Island Unknown Arctic Wrangel Island ENVELOPE(-179.385,-179.385,71.244,71.244)
institution Open Polar
collection Unknown
op_collection_id ftciteseerx
language English
topic change-point
spellingShingle change-point
Naoki Itoh
Jürgen Kurths
Change-Point Detection of Climate Time Series by Nonparametric Method
topic_facet change-point
description Abstract—In one of the data mining techniques, change-point detection is of importance in evaluating time series measured in real world. For decades this technique has been developed as a nonlinear dynamics. We apply the method for detecting the change points, Singular Spectrum Transformation (SST), to the climate time series. To know where the structures of climate data sets change can reveal a climate background. In this paper we discuss the structures of precipitation data in Kenya and Wrangel Island (Arctic land) by using the SST.
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author Naoki Itoh
Jürgen Kurths
author_facet Naoki Itoh
Jürgen Kurths
author_sort Naoki Itoh
title Change-Point Detection of Climate Time Series by Nonparametric Method
title_short Change-Point Detection of Climate Time Series by Nonparametric Method
title_full Change-Point Detection of Climate Time Series by Nonparametric Method
title_fullStr Change-Point Detection of Climate Time Series by Nonparametric Method
title_full_unstemmed Change-Point Detection of Climate Time Series by Nonparametric Method
title_sort change-point detection of climate time series by nonparametric method
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.4237
http://www.iaeng.org/publication/WCECS2010/WCECS2010_pp445-448.pdf
long_lat ENVELOPE(-179.385,-179.385,71.244,71.244)
geographic Arctic
Wrangel Island
geographic_facet Arctic
Wrangel Island
genre Arctic
Wrangel Island
genre_facet Arctic
Wrangel Island
op_source http://www.iaeng.org/publication/WCECS2010/WCECS2010_pp445-448.pdf
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.4237
http://www.iaeng.org/publication/WCECS2010/WCECS2010_pp445-448.pdf
op_rights Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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