On the convergence of finite linear predictors of stationary processes

It is shown that the finite linear least-squares predictor of a multivariate stationary process converges to its Kolmogorov-Wiener predictor at an exponential rate, provided that the entries of its spectral density matrix are smooth functions. Also, the same rate of convergence holds for the partial sums of the Kolmogorov-Wiener predictor.

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Year of publication:	1989
Authors:	Pourahmadi, Mohsen
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 30.1989, 2, p. 167-180
Publisher:	Elsevier
Keywords:	q-variate stationary processes linear predictor prediction error exponential rate of convergence analytic

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005160491