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R.M. Dünki & M. Dressel, PHYSICA A 370: 632 - 650 (2006)
The analysis of records of biophysical signals like EEG has become increasingly interesting
to physicists since the development of new algorithms for time series analysis. This analysis
however, requires both - an adequate methodology assessing the time series characteristics
and an appropriate statistical assessment of the measures resulting from these algorithms.
The latter should separate inherent effects from those appearing only by chance, e.g., in
terms of an appropriate test statistics. As a step towards such a statistical assessment
we present here a data resampling approach: Data resampling techniques allow for the
estimation of the variance of an F-value as obtained through variance analysis. A test
statistics based on so-called F-ratios (F)/F
is derived and the simulation of outcomes
allows for the determination of quantiles. A multivariate formulation allows for the
simultaneous inclusion of linear and nonlinear time series-measures into the analysis.
We applied these concepts to the problem of distinguishing EEG of healthy probands from
the EEG of patients diagnosed as schizophrenic. Together with an approach involving Bayes
formula to weight the variables, it reveals a reliable discrimination performance of 81 % when
the nonlinear measure and the linear measures
- and
-power are included.
Ruedi Duenki
Mon Sep 11 13:31:26 MET 2006