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Vector Autoregressive Model-Order Selection From Finite Samples Using Kullback's Symmetric Divergence

Seghouane, Abd-Krim


In this paper, a new small-sample model selection criterion for vector autoregressive (VAR) models is developed. The proposed criterion is named Kullback information criterion (KICvc), where the notation vc stands for vector correction, and it can be considered as an extension of the KIC, for VAR models. KICvc adjusts KIC to be an unbiased estimator for the variant of the Kullback symmetric divergence, assuming that the true model is correctly specified or overfitted. Furthermore, KICvc...[Show more]

CollectionsANU Research Publications
Date published: 2006
Type: Journal article
Source: IEEE Transactions on Circuits and Systems 1:FUNDAMENTAL THEORY AND APPLICATIONS
DOI: 10.1109/TCSI.2006.883158


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