Estimation of Time Series Models via Robust Wavelet Variance

A robust approach to the estimation of time series models is proposed. Taking from a new estimation method called the Generalized Method of Wavelet Moments (GMWM) which is an indirect method based on the Wavelet Variance (WV), we replace the classical estimator of the WV with a recently proposed ro...

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Main Authors:	Stephane Guerrier, Roberto Molinari, Maria-Pia Victoria-Feser
Format:	Article
Language:	English
Published:	Austrian Statistical Society 2014-06-01
Series:	Austrian Journal of Statistics
Online Access:	http://www.ajs.or.at/index.php/ajs/article/view/45

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spelling	doaj-8ee34c6ff3424e258ade4a4702eacff02021-04-22T12:35:11ZengAustrian Statistical SocietyAustrian Journal of Statistics1026-597X2014-06-0143410.17713/ajs.v43i4.4522Estimation of Time Series Models via Robust Wavelet VarianceStephane Guerrier0Roberto Molinari1Maria-Pia Victoria-Feser2University of California, Santa BarbaraUniversite de GeneveUniversite de Geneve A robust approach to the estimation of time series models is proposed. Taking from a new estimation method called the Generalized Method of Wavelet Moments (GMWM) which is an indirect method based on the Wavelet Variance (WV), we replace the classical estimator of the WV with a recently proposed robust M-estimator to obtain a robust version of the GMWM. The simulation results show that the proposed approach can be considered as a valid robust approach to the estimation of time series and state-space models. http://www.ajs.or.at/index.php/ajs/article/view/45
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Stephane Guerrier Roberto Molinari Maria-Pia Victoria-Feser
spellingShingle	Stephane Guerrier Roberto Molinari Maria-Pia Victoria-Feser Estimation of Time Series Models via Robust Wavelet Variance Austrian Journal of Statistics
author_facet	Stephane Guerrier Roberto Molinari Maria-Pia Victoria-Feser
author_sort	Stephane Guerrier
title	Estimation of Time Series Models via Robust Wavelet Variance
title_short	Estimation of Time Series Models via Robust Wavelet Variance
title_full	Estimation of Time Series Models via Robust Wavelet Variance
title_fullStr	Estimation of Time Series Models via Robust Wavelet Variance
title_full_unstemmed	Estimation of Time Series Models via Robust Wavelet Variance
title_sort	estimation of time series models via robust wavelet variance
publisher	Austrian Statistical Society
series	Austrian Journal of Statistics
issn	1026-597X
publishDate	2014-06-01
description	A robust approach to the estimation of time series models is proposed. Taking from a new estimation method called the Generalized Method of Wavelet Moments (GMWM) which is an indirect method based on the Wavelet Variance (WV), we replace the classical estimator of the WV with a recently proposed robust M-estimator to obtain a robust version of the GMWM. The simulation results show that the proposed approach can be considered as a valid robust approach to the estimation of time series and state-space models.
url	http://www.ajs.or.at/index.php/ajs/article/view/45
work_keys_str_mv	AT stephaneguerrier estimationoftimeseriesmodelsviarobustwaveletvariance AT robertomolinari estimationoftimeseriesmodelsviarobustwaveletvariance AT mariapiavictoriafeser estimationoftimeseriesmodelsviarobustwaveletvariance
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Estimation of Time Series Models via Robust Wavelet Variance

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