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Abstract
The problem of estimating spectral density of a nonstationary process satisfying local stationarity conditions is considered. The proposed solution is a two step procedure based on local autoregressive (AR) modeling. In the first step Bayesian-like averaging of AR models, differing in order, is performed. The main contribution of the paper is development of a new final-prediction-error-like statistic, which can be used to select optimal estimation bandwidth in the second step of the procedure. Simulation experiments demonstrate that the combined cooperative-competitive approach outperforms the previously introduced fully competitive scheme.
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- Accepted or Published Version
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- Copyright (2017 IEEE)
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- Category:
- Conference activity
- Type:
- materiały konferencyjne indeksowane w Web of Science
- Title of issue:
- 2017 IEEE 56th Annual Conference on Decision and Control (CDC) strony 3600 - 3605
- Language:
- English
- Publication year:
- 2017
- Bibliographic description:
- Meller M., Niedźwiecki M., Chojnacki D., Lasota A..: On autoregressive spectrum estimation using the model averaging technique, W: 2017 IEEE 56th Annual Conference on Decision and Control (CDC), 2017, Institute of Electrical and Electronics Engineers (IEEE),.
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/cdc.2017.8264188
- Verified by:
- Gdańsk University of Technology
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