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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes

Abstract

The problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.

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Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
IEEE TRANSACTIONS ON SIGNAL PROCESSING no. 67, pages 769 - 782,
ISSN: 1053-587X
Language:
English
Publication year:
2019
Bibliographic description:
Niedźwiecki M., Ciołek M.: On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes// IEEE TRANSACTIONS ON SIGNAL PROCESSING. -Vol. 67, iss. 3 (2019), s.769-782
DOI:
Digital Object Identifier (open in new tab) 10.1109/tsp.2018.2885480
Verified by:
Gdańsk University of Technology

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