Aquileo | statsmodels.durbin_watson() in Python

With the help of statsmodels.durbin_watson() method, we can get the durbin watson test statistics and it is equal to 2*(1-r), where r is autocorrelation between residual.

Syntax : statsmodels.durbin_watson(residual) Return : Return a single floating point value of durbin watson.

Example #1 : In this example we can see that by using statsmodels.durbin_watson() method, we are able to get the durbin watson test statistical value by using this method.

Python3 1=1

# import numpy and statsmodels
import numpy as np
from statsmodels.stats.stattools import durbin_watson

g = np.array([1, 2, 3])
# Using statsmodels.durbin_watson() method
gfg = durbin_watson(g)

print(gfg)

Output :

0.14285714285714285

Example #2 :

Python3 1=1

# import numpy and statsmodels
import numpy as np
from statsmodels.stats.stattools import durbin_watson

g = np.array([1, 2, 3, 4, -3, -2, -1])
# Using statsmodels.durbin_watson() method
gfg = durbin_watson(g)

print(gfg)

Output :

1.2272727272727273

statsmodels.durbin_watson() in Python

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