Python – ksone Distribution in Statistics
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
from scipy.stats import ksone
numargs = ksone.numargs
a, b = 4.32 , 3.18
rv = ksone(a, b)
print ( "RV : \n" , rv)
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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 )
R = ksone.rvs(a, b, scale = 2 , size = 10 )
print ( "Random Variates : \n" , R)
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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))
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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 )
y1 = ksone.pdf(x, 1 , 3 )
y2 = ksone.pdf(x, 1 , 4 )
plt.plot(x, y1, "*" , x, y2, "r--" )
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Output :
Last Updated :
10 Jan, 2020
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