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Some cycles/ARs are almost zero. Detect this earlier and decrease the number of candidates accordingly. This is a small optimization.
Can discard all cycles if the trend residue is small (max - min < 0.001).
Can discard all ARs if the cycle residue is small (max - min < 0.001).
the criterion (max - min < 0.001) has to be kept as simple as possible for robustness. Do not take into account outliers etc (this is a different task and needs some real work).
The threshold 0.001 is reasonable as the signal is re-scaled (to be in [0, 1]) based on min/max before each transformation.
The text was updated successfully, but these errors were encountered:
Some cycles/ARs are almost zero. Detect this earlier and decrease the number of candidates accordingly. This is a small optimization.
Can discard all cycles if the trend residue is small (max - min < 0.001).
Can discard all ARs if the cycle residue is small (max - min < 0.001).
the criterion (max - min < 0.001) has to be kept as simple as possible for robustness. Do not take into account outliers etc (this is a different task and needs some real work).
The threshold 0.001 is reasonable as the signal is re-scaled (to be in [0, 1]) based on min/max before each transformation.
The text was updated successfully, but these errors were encountered: