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Python – Kolmogorov-Smirnov Distribution in Statistics

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scipy.stats.kstwobign() is Kolmogorov-Smirnov two-sided test for large N test that is defined with a standard format and some shape parameters to complete its specification. It is a statistical test that measures the maximum absolute distance of the theoretical CDF from the empirical CDF.

Parameters :

q : lower and upper tail probability
x : quantiles
loc : [optional]location parameter. Default = 0
scale : [optional]scale parameter. Default = 1
size : [tuple of ints, optional] shape or random variates.

Results : kstwobign continuous random variable

Code #1 : Creating kstwobign continuous random variable




# importing library
  
from scipy.stats import kstwobign  
    
numargs = kstwobign.numargs 
a, b = 4.32, 3.18
rv = kstwobign(a, b) 
    
print ("RV : \n", rv)  
  


Output :

RV : 
 scipy.stats._distn_infrastructure.rv_frozen object at 0x000002A9D54959C8


Code #2 : kstwobign continuous variates and probability distribution




import numpy as np 
quantile = np.arange (0.01, 1, 0.1
  
# Random Variates 
R = kstwobign.rvs(a, b, scale = 2, size = 10
print ("Random Variates : \n", R) 


Output :

Random Variates : 
 [3.88510141 3.48394857 3.66124797 3.88484201 3.86533511 3.21176073
 4.10238585 3.42397866 3.85111721 4.36433596]

Code #3 : Graphical Representation.




import numpy as np 
import matplotlib.pyplot as plt 
     
distribution = np.linspace(0, np.minimum(rv.dist.b, 3)) 
print("Distribution : \n", distribution) 
     
plot = plt.plot(distribution, rv.pdf(distribution)) 


Output :

Distribution : 
 [0.         0.06122449 0.12244898 0.18367347 0.24489796 0.30612245
 0.36734694 0.42857143 0.48979592 0.55102041 0.6122449  0.67346939
 0.73469388 0.79591837 0.85714286 0.91836735 0.97959184 1.04081633
 1.10204082 1.16326531 1.2244898  1.28571429 1.34693878 1.40816327
 1.46938776 1.53061224 1.59183673 1.65306122 1.71428571 1.7755102
 1.83673469 1.89795918 1.95918367 2.02040816 2.08163265 2.14285714
 2.20408163 2.26530612 2.32653061 2.3877551  2.44897959 2.51020408
 2.57142857 2.63265306 2.69387755 2.75510204 2.81632653 2.87755102
 2.93877551 3.        ]
 

Code #4 : Varying Positional Arguments




import matplotlib.pyplot as plt 
import numpy as np 
     
x = np.linspace(0, 5, 100
     
# Varying positional arguments 
y1 = kstwobign .pdf(x, 1, 3
y2 = kstwobign .pdf(x, 1, 4
plt.plot(x, y1, "*", x, y2, "r--"


Output :



Last Updated : 10 Jan, 2020
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