Multivariate analysis of dynamical processes |
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Authors: | K Henschel B Hellwig F Amtage J Vesper M Jachan C H Lücking J Timmer B Schelter |
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Institution: | (1) Applied Statistics Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata, 700 108, India;(2) School of Mathematics, University of Birmingham, Watson Building, Birmingham, B15 2TT, UK |
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Abstract: | The analysis of multi-dimensional biomedical systems requires analysis techniques, which are able to deal with multivariate
data consisting of both time series as well as point processes. Univariate and bivariate analysis techniques in the frequency
domain for time series and point processes are established and investigated, although the number of investigations is strongly
biased towards time series. Actual multivariate techniques for time series or hybrids of time series and point processes are
scarcely addressed. Here, we present spectral analysis techniques which are able to analyse point processes as well as time
series. Thereby, univariate, bivariate as well as multivariate techniques are discussed. Applications to simulated as well
as real-world data reveal the abilities of the proposed techniques. |
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Keywords: | |
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