Multivariate time series analysis. (English) Zbl 1272.62061
Dahlhaus, Rainer (ed.) et al., Mathematical methods in signal processing and digital image analysis. Berlin: Springer (ISBN 978-3-540-75631-6/hbk). Springer Complexity, 1-40 (2008).
Summary: Nowadays, modern measurement devices are capable to deliver signals with increasing data rates and higher spatial resolutions. When analyzing these data, particular interest is focused on disentangling the network structure underlying the recorded signals. Neither univariate nor bivariate analysis techniques are expected to describe the interactions between the processes sufficiently well. Moreover, the direction of the direct interactions is particularly important to understand the underlying network structure sufficiently well. Here, we present multivariate approaches to time series analysis being able to distinguish direct and indirect, in some cases the directions of interactions in linear as well as nonlinear systems.
For the entire collection see [Zbl 1130.68006].
For the entire collection see [Zbl 1130.68006].
MSC:
| 62M10 | Time series, auto-correlation, regression, etc. in statistics (GARCH) |
| 37M10 | Time series analysis of dynamical systems |
| 62P10 | Applications of statistics to biology and medical sciences; meta analysis |
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