Scientific article
English

Estimation of Time Series Models via Robust Wavelet Variance

Published inÖsterreichische Zeitschrift für Statistik, vol. 43, no. 3-4, p. 267-277
Publication date2014
Abstract

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.

Keywords
  • Maximum overlap discrete transform
  • M-estimator
  • Generalized method of wavelet moments
  • Composite stochastic processes
  • Autoregressive processes
Citation (ISO format)
GUERRIER, Stéphane, MOLINARI, Roberto Carlo, VICTORIA-FESER, Maria-Pia. Estimation of Time Series Models via Robust Wavelet Variance. In: Österreichische Zeitschrift für Statistik, 2014, vol. 43, n° 3-4, p. 267–277. doi: 10.17713/ajs.v43i4.45
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Article (Published version)
accessLevelRestricted
Identifiers
Journal ISSN1026-597X
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Technical informations

Creation19/06/2014 13:58:00
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