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Abstract
Autoregressive modeling is a widespread parametricspectrum estimation method. It is well known that, in the caseof stationary processes with unknown order, its accuracy canbe improved by averaging models of different complexity usingsuitably chosen weights. The paper proposes an extension of thistechnique to the case of multivariate locally stationary processes.The proposed solution is based on local autoregressive modeling,and combines model averaging with estimation bandwidth adap-tation. Results of simulations demonstrate that the application ofthe proposed decision rules allows one to outperform the standardapproach, which does not include the bandwidth adaptation.
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- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language:
- English
- Publication year:
- 2019
- Bibliographic description:
- Meller M., Niedźwiecki M., Chojnacki D.: On Adaptive Spectrum Estimation of Multivariate Autoregressive Locally Stationary Processes// / : , 2019,
- DOI:
- Digital Object Identifier (open in new tab) 10.23919/eusipco.2019.8902751
- Verified by:
- Gdańsk University of Technology
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