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Python – ksone Distribution in Statistics

  • Last Updated : 10 Jan, 2020

scipy.stats.ksone() is a General Kolmogorov-Smirnov one-sided test that is defined with a standard format and some shape parameters to complete its specification. It is a statistical test for the finite sample size n.

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.
moments : [optional] composed of letters [‘mvsk’]; ‘m’ = mean, ‘v’ = variance, ‘s’ = Fisher’s skew and ‘k’ = Fisher’s kurtosis. (default = ‘mv’).

Results : ksone continuous random variable

Code #1 : Creating ksone continuous random variable






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

Output :

RV : 
 scipy.stats._distn_infrastructure.rv_frozen object at 0x000002A9D530AB48


Code #2 : Ksone continuous variates and probability distribution




import numpy as np 
quantile = np.arange (0.01, 1, 0.1
  
# Random Variates 
R = ksone.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.         0.02040816 0.04081633 0.06122449 0.08163265 0.10204082
 0.12244898 0.14285714 0.16326531 0.18367347 0.20408163 0.2244898
 0.24489796 0.26530612 0.28571429 0.30612245 0.32653061 0.34693878
 0.36734694 0.3877551  0.40816327 0.42857143 0.44897959 0.46938776
 0.48979592 0.51020408 0.53061224 0.55102041 0.57142857 0.59183673
 0.6122449  0.63265306 0.65306122 0.67346939 0.69387755 0.71428571
 0.73469388 0.75510204 0.7755102  0.79591837 0.81632653 0.83673469
 0.85714286 0.87755102 0.89795918 0.91836735 0.93877551 0.95918367
 0.97959184 1.        ]
 

Code #4 : Varying Positional Arguments




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

Output :




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