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Springer Characterizing Interdependencies of Multiple Time Series: Theory and Applications (SpringerBriefs in Statistics)

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Description

Presents an approach to characterizing the interdependencies of multivariate time series by means of the basic concept of the one-way effect Shows how the third-series effect is eliminated with least causal distortion, introducing partial measures of the one-way effect, reciprocity, and association Illustrates the proposed causal characterization by means of empirical applications to real data sets of the US macroeconomy and Japan’s financial economy

Product Specifications

Colour
White
Format
paperback
Domain
Amazon UK
Release Date
08 November 2017
Listed Since
25 July 2017

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