A propagation-separation approach to estimate the autocorrelation in a time-series

The paper presents an approach to estimate parameters of a local stationary AR(1) time series model by maximization of a local likelihood function. The method is based on a propagation-separation procedure that leads to data dependent weights defining the local model. Using free propagation of weigh...

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Main Authors: Divine, D.V., Polzehl, J., Godtliebsen, F.
Format: Article in Journal/Newspaper
Language:English
Published: Göttingen : Copernicus 2008
Subjects:
530
Online Access:https://doi.org/10.34657/4139
https://oa.tib.eu/renate/handle/123456789/5510
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spelling ftleibnizopen:oai:oai.leibnizopen.de:JS_SeYsBBwLIz6xGce-T 2023-11-12T04:22:09+01:00 A propagation-separation approach to estimate the autocorrelation in a time-series Divine, D.V. Polzehl, J. Godtliebsen, F. 2008 application/pdf https://doi.org/10.34657/4139 https://oa.tib.eu/renate/handle/123456789/5510 eng eng Göttingen : Copernicus CC BY 3.0 Unported https://creativecommons.org/licenses/by/3.0/ Nonlinear Processes in Geophysics 15 (2008), Nr. 4 El Nino-Southern Oscillation estimation method GRIP hydrological modeling North Atlantic Oscillation reconstruction stable isotope time series 530 article Text 2008 ftleibnizopen https://doi.org/10.34657/4139 2023-10-30T00:19:14Z The paper presents an approach to estimate parameters of a local stationary AR(1) time series model by maximization of a local likelihood function. The method is based on a propagation-separation procedure that leads to data dependent weights defining the local model. Using free propagation of weights under homogeneity, the method is capable of separating the time series into intervals of approximate local stationarity. Parameters in different regions will be significantly different. Therefore the method also serves as a test for a stationary AR(1) model. The performance of the method is illustrated by applications to both synthetic data and real time-series of reconstructed NAO and ENSO indices and GRIP stable isotopes. publishedVersion Article in Journal/Newspaper North Atlantic North Atlantic oscillation Unknown
institution Open Polar
collection Unknown
op_collection_id ftleibnizopen
language English
topic El Nino-Southern Oscillation
estimation method
GRIP
hydrological modeling
North Atlantic Oscillation
reconstruction
stable isotope
time series
530
spellingShingle El Nino-Southern Oscillation
estimation method
GRIP
hydrological modeling
North Atlantic Oscillation
reconstruction
stable isotope
time series
530
Divine, D.V.
Polzehl, J.
Godtliebsen, F.
A propagation-separation approach to estimate the autocorrelation in a time-series
topic_facet El Nino-Southern Oscillation
estimation method
GRIP
hydrological modeling
North Atlantic Oscillation
reconstruction
stable isotope
time series
530
description The paper presents an approach to estimate parameters of a local stationary AR(1) time series model by maximization of a local likelihood function. The method is based on a propagation-separation procedure that leads to data dependent weights defining the local model. Using free propagation of weights under homogeneity, the method is capable of separating the time series into intervals of approximate local stationarity. Parameters in different regions will be significantly different. Therefore the method also serves as a test for a stationary AR(1) model. The performance of the method is illustrated by applications to both synthetic data and real time-series of reconstructed NAO and ENSO indices and GRIP stable isotopes. publishedVersion
format Article in Journal/Newspaper
author Divine, D.V.
Polzehl, J.
Godtliebsen, F.
author_facet Divine, D.V.
Polzehl, J.
Godtliebsen, F.
author_sort Divine, D.V.
title A propagation-separation approach to estimate the autocorrelation in a time-series
title_short A propagation-separation approach to estimate the autocorrelation in a time-series
title_full A propagation-separation approach to estimate the autocorrelation in a time-series
title_fullStr A propagation-separation approach to estimate the autocorrelation in a time-series
title_full_unstemmed A propagation-separation approach to estimate the autocorrelation in a time-series
title_sort propagation-separation approach to estimate the autocorrelation in a time-series
publisher Göttingen : Copernicus
publishDate 2008
url https://doi.org/10.34657/4139
https://oa.tib.eu/renate/handle/123456789/5510
genre North Atlantic
North Atlantic oscillation
genre_facet North Atlantic
North Atlantic oscillation
op_source Nonlinear Processes in Geophysics 15 (2008), Nr. 4
op_rights CC BY 3.0 Unported
https://creativecommons.org/licenses/by/3.0/
op_doi https://doi.org/10.34657/4139
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