On relations between prediction error covariance of univariate and multivariate processes

Mohsen Pourahmadi

Statistics & Probability Letters, 1993, vol. 16, issue 5, 355-359

Abstract: By using results pertaining to prediction of univariate stationary processes we express [Sigma], the one-step ahead prediction error covariance matrix of a multivariate procces in terms of its spectral density matrix [latin small letter f with hook]x. This sheds some light on a problem of Wiener and Masani (1957). Alternatively, by relying on results from interpolation of multivariate processes, we obtain closed-form and applicable formulae for the interpolators and their errors for a stretch of missing values of univariate processes.

Keywords: Prediction; error; covariance; matrix; spectral; density; interpolation; of; missing; values (search for similar items in EconPapers)
Date: 1993
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