`scipy.stats._probability_distribution:_ProbabilityDistribution.kurtosis`

source: /scipy/stats/_probability_distribution.py :656

Signature

def kurtosis ( self , * , method )

Summary

Kurtosis (standardized fourth moment)

Extended Summary

By default, this is the standardized fourth moment, also known as the "non-excess" or "Pearson" kurtosis (e.g. the kurtosis of the normal distribution is 3). The "excess" or "Fisher" kurtosis (the standardized fourth moment minus 3) is available via the convention parameter.

Parameters

method : {None, 'formula', 'general', 'transform', 'normalize', 'cache'}

Method used to calculate the standardized fourth moment. Not all methods are available for all distributions. See moment for details.

convention : {'non-excess', 'excess'}

Two distinct conventions are available:

'non-excess': the standardized fourth moment (Pearson's kurtosis)
'excess': the standardized fourth moment minus 3 (Fisher's kurtosis)

The default is 'non-excess'.

Examples

Instantiate a distribution with the desired parameters:

from scipy import stats
X = stats.Normal(mu=1., sigma=2.)

✓

Evaluate the kurtosis:

X.kurtosis()
(X.kurtosis()
 == X.kurtosis(convention='excess') + 3.
 == X.moment(order=4, kind='standardized'))

✗

Aliases

scipy.stats._distribution_infrastructure._ProbabilityDistribution.kurtosis