Kurtosis¶
Running kurtosis using Welford's algorithm.
Parameters¶
-
bias – defaults to
FalseIf
False, then the calculations are corrected for statistical bias.
Attributes¶
- name
Examples¶
>>> from river import stats
>>> import scipy.stats
>>> import numpy as np
>>> np.random.seed(42)
>>> X = np.random.normal(loc=0, scale=1, size=10)
>>> kurtosis = stats.Kurtosis(bias=False)
>>> for x in X:
... print(kurtosis.update(x).get())
-3.0
-2.0
-1.5
1.4130027920707047
0.15367976585756438
0.46142633246812653
-1.620647789230658
-1.3540178492487054
-1.2310268787102745
-0.9490372374384453
>>> for i in range(2, len(X)+1):
... print(scipy.stats.kurtosis(X[:i], bias=False))
-2.0
-1.4999999999999998
1.4130027920707082
0.15367976585756082
0.46142633246812403
-1.620647789230658
-1.3540178492487063
-1.2310268787102738
-0.9490372374384459
>>> kurtosis = stats.Kurtosis(bias=True)
>>> for x in X:
... print(kurtosis.update(x).get())
-3.0
-2.0
-1.5
-1.011599627723906
-0.9615800585356089
-0.6989395431537853
-1.4252699121794408
-1.311437071070812
-1.246289111322894
-1.082283689864171
>>> for i in range(2, len(X)+1):
... print(scipy.stats.kurtosis(X[:i], bias=True))
-2.0
-1.4999999999999998
-1.0115996277239057
-0.9615800585356098
-0.6989395431537861
-1.425269912179441
-1.3114370710708125
-1.2462891113228936
-1.0822836898641714
Methods¶
get
Return the current value of the statistic.
update
Update and return the called instance.
Parameters
- x (numbers.Number)