statsmodels.robust_kurtosis() in Python (original) (raw)

Last Updated : 10 May, 2020

With the help of **statsmodels.robust_kurtosis()** method, we can calculate the four kurtosis value by using statsmodels.robust_kurtosis() method.

Syntax : statsmodels.robust_kurtosis(numpy_array) Return : Return four value of kurtosis i.e kr1, kr2, kr3 and kr4.

**Example #1 :**In this example we can see that by using statsmodels.robust_kurtosis() method, we are able to get the four kurtosis value of a numpy array by using this method.

Python3 1=1 `

import numpy and statsmodels

import numpy as np from statsmodels.stats.stattools import robust_kurtosis

g = np.array([1, 2, 3, 4, 7, 8])

Using statsmodels.robust_kurtosis() method

gfg = robust_kurtosis(g)

print(gfg)

`

Output :

(-1.3893422240232831, -0.17059511548521722, -0.9698425074861872, -1.218346951670164)

Example #2 :

Python3 1=1 `

import numpy and statsmodels

import numpy as np from statsmodels.stats.stattools import robust_kurtosis

g = np.array([1, 2, 8, 9, 10])

Using statsmodels.robust_kurtosis() method

gfg = robust_kurtosis(g)

print(gfg)

`

Output :

(-1.7408163265306122, -0.5902379726280743, -1.4602271228708026, -1.6487040945273066)