We cast the problem of determining phenotypic models as that of finding representative time series for each phenotype cluster in the data.
Time series for each feature are processed in parallel using dynamic time warping (DTW), which measures the similarity between two time series after finding an optimal match between them by 'warping' the time axis [45].
Basic facts and time series for macroeconomics.
Indeed, the whole time series for Greece is zero.
Figure 8 Experiment A: SNR time series for PRN 25.
Figure 2 Time series for flu (a) and unemployment (b).
We also did statistical models without adjusting for time trends and used the longest time series available from 1993, finding similar results (web appendix 4).
Lower bounding The technique uses cheap-to-compute lower bounding functions to reduce the number of times computing the DTW distance for finding the time-series sequence that is nearly similar to a given time-series pattern.
To give an example, here are the individual electrode Z-statistic time-series for chosen value, which comprise the findings for the DLPFC, OFC and ACC electrodes in Figure 1D and Figure 1 figure supplement 3.
Since the parasite identified using the sketch shows greater mobility than the one obtained using DTW+MSD, we postulate that sketching may be a better approach for finding representative time series.
