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Titel |
Time series segmentation with shifting means hidden markov models |
VerfasserIn |
Ath. Kehagias, V. Fortin |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1023-5809
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Digitales Dokument |
URL |
Erschienen |
In: Nonlinear Processes in Geophysics ; 13, no. 3 ; Nr. 13, no. 3 (2006-08-01), S.339-352 |
Datensatznummer |
250011778
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Publikation (Nr.) |
copernicus.org/npg-13-339-2006.pdf |
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Zusammenfassung |
We present a new family of hidden Markov models and apply these to the
segmentation of hydrological and environmental time series. The proposed
hidden Markov models have a discrete state space and their structure is
inspired from the shifting means models introduced by Chernoff and
Zacks and by Salas and Boes. An estimation method inspired from the EM
algorithm is proposed, and we show that it can accurately identify multiple
change-points in a time series. We also show that the solution obtained using
this algorithm can serve as a starting point for a Monte-Carlo Markov chain
Bayesian estimation method, thus reducing the computing time needed for the
Markov chain to converge to a stationary distribution. |
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