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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes

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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DOI
Digital Object Identifier link open in new tab 10.1109/tsp.2018.2885480
Category
Publikacja w czasopiśmie
Type
artykuł w czasopiśmie wyróżnionym w JCR
Language
angielski
Publication year
2019

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