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Prediction of Time Series

Authors: Masanao Aoki;

Prediction of Time Series

Abstract

The covariance matrix of a stacked data vector (y1′, y2′, ... yn′)′ of a meanzero weakly stationary process {yt} has a special structure: A submatrix Λ0 =Ey1y1′ is located along the main diagonal, the matrix \({\Lambda _\ell } = E{y_{\ell + 1}}{y'_1}\) along the \( \ell\)-th diagonal below the main diagonal, and \({\Lambda _{ - \ell }} = E{y_1}{y'_{\ell + 1}} = {\Lambda '_\ell }\) along the \(\ell\)-th diagonal above the main diagonal. This covariance matrix is a block Toeplitz matrix because the same submatrices are arranged in the same way that elements are arranged in Toeplitz matrices.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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