Abstract:We consider a multi-variate system Y t = AX t , where the unobserved components X t are independent AR(1) processes and the number of sources is greater than the number of observed outputs. We show that the mixing matrix A, the AR(1) coefficients and distributions of X t can be identified (up to scale factors of X t ), which solves the dynamic deconvolution problem. The proof is constructive and allows us to introduce simple consistent estimators of all unknown scalar and functional parameters of the model. Th… Show more
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