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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Austrian Statistical Society
2014-06-01
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| Series: | Austrian Journal of Statistics |
| Online Access: | http://www.ajs.or.at/index.php/ajs/article/view/45 |
| Summary: | 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.
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| ISSN: | 1026-597X |