turbustat.statistics.
Tsallis_Distance
(array1, array2, lags=None, num_bins=500, fiducial_model=None, periodic=False)[source] [edit on github]¶Bases: object
Distance Metric for the Tsallis Distribution.
Parameters: | array1 : numpy.ndarray
array2 : numpy.ndarray
lags : numpy.ndarray or list
num_bins : int, optional
fiducial_model : Tsallis
periodic : bool, optional
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Methods Summary
Methods Documentation
distance_metric
(verbose=False)[source] [edit on github]¶We do not consider the parameter a in the distance metric. Since we are fitting to a PDF, a is related to the number of data points and is therefore not a true measure of the differences between the data sets. The distance is computed by summing the squared difference of the parameters, normalized by the sums of the squares, for each lag. The total distance the sum between the two parameters.
Parameters: | verbose : bool, optional
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