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

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: D. V. Divine, J. Polzehl, F. Godtliebsen
Format: Article
Language:English
Published: Copernicus Publications 2008-07-01
Series:Nonlinear Processes in Geophysics
Online Access:http://www.nonlin-processes-geophys.net/15/591/2008/npg-15-591-2008.pdf
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spelling doaj-082128b42bc14ae0ad681bace526da8c2020-11-25T01:45:48ZengCopernicus PublicationsNonlinear Processes in Geophysics1023-58091607-79462008-07-01154591599A propagation-separation approach to estimate the autocorrelation in a time-seriesD. V. DivineJ. PolzehlF. GodtliebsenThe 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. http://www.nonlin-processes-geophys.net/15/591/2008/npg-15-591-2008.pdf
collection DOAJ
language English
format Article
sources DOAJ
author D. V. Divine
J. Polzehl
F. Godtliebsen
spellingShingle D. V. Divine
J. Polzehl
F. Godtliebsen
A propagation-separation approach to estimate the autocorrelation in a time-series
Nonlinear Processes in Geophysics
author_facet D. V. Divine
J. Polzehl
F. Godtliebsen
author_sort D. V. Divine
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 Copernicus Publications
series Nonlinear Processes in Geophysics
issn 1023-5809
1607-7946
publishDate 2008-07-01
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.
url http://www.nonlin-processes-geophys.net/15/591/2008/npg-15-591-2008.pdf
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