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Module « scipy.stats.mstats »

Fonction kurtosis - module scipy.stats.mstats

Signature de la fonction kurtosis

def kurtosis(a, axis=0, fisher=True, bias=True) 

Description

help(scipy.stats.mstats.kurtosis)

Computes the kurtosis (Fisher or Pearson) of a dataset.

Kurtosis is the fourth central moment divided by the square of the
variance. If Fisher's definition is used, then 3.0 is subtracted from
the result to give 0.0 for a normal distribution.

If bias is False then the kurtosis is calculated using k statistics to
eliminate bias coming from biased moment estimators

Use `kurtosistest` to see if result is close enough to normal.

Parameters
----------
a : array
    data for which the kurtosis is calculated
axis : int or None, optional
    Axis along which the kurtosis is calculated. Default is 0.
    If None, compute over the whole array `a`.
fisher : bool, optional
    If True, Fisher's definition is used (normal ==> 0.0). If False,
    Pearson's definition is used (normal ==> 3.0).
bias : bool, optional
    If False, then the calculations are corrected for statistical bias.

Returns
-------
kurtosis : array
    The kurtosis of values along an axis. If all values are equal,
    return -3 for Fisher's definition and 0 for Pearson's definition.

Notes
-----
For more details about `kurtosis`, see `scipy.stats.kurtosis`.

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