kurtosis#
- Uniform.kurtosis(*, method=None, convention='non-excess')[source]#
- Kurtosis (standardized fourth moment) - 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 - momentfor 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'.
 
 - References [1]- Kurtosis, Wikipedia, https://en.wikipedia.org/wiki/Kurtosis - Examples - Instantiate a distribution with the desired parameters: - >>> from scipy import stats >>> X = stats.Normal(mu=1., sigma=2.) - Evaluate the kurtosis: - >>> X.kurtosis() 3.0 >>> (X.kurtosis() ... == X.kurtosis(convention='excess') + 3. ... == X.moment(order=4, kind='standardized')) True