pyhctsa.operations.stationarity.dyn_win¶
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pyhctsa.operations.stationarity.dyn_win(y, max_num_segments=
10)¶ How stationarity estimates depend on the number of time-series subsegments.
Specifically, variation in a range of local measures are implemented: mean, standard deviation, skewness, kurtosis, ApEn(1,0.2), SampEn(1,0.2), AC(1), AC(2), and the first zero-crossing of the autocorrelation function.
The standard deviation of local estimates of these quantities across the time series are calculated as an estimate of the stationarity in this quantity as a function of the number of splits, n_{seg}, of the time series.