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scipy stats.halfcauchy() | Python

scipy.stats.halfcauchy() is an Half-Cauchy continuous random variable that is defined with a standard format and some shape parameters to complete its specification.

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 : Half-Cauchy continuous random variable

Code #1 : Creating Half-Cauchy continuous random variable




from scipy.stats import halfcauchy  
  
numargs = halfcauchy.numargs
[] = [0.7, ] * numargs
rv = halfcauchy)
  
print ("RV : \n", rv) 


Output :

RV : 
 <scipy.stats._distn_infrastructure.rv_frozen object at 0x000001E39A272470>

Code #2 : Half-Cauchy random variates and probability distribution




import numpy as np
quantile = np.arange (0.01, 1, 0.1)
   
# Random Variates
R = halfcauchy.rvs(scale = 2,  size = 10)
print ("Random Variates : \n", R)
  
# PDF
R = halfcauchy.pdf(quantile, loc = 0, scale = 1)
print ("\nProbability Distribution : \n", R)


Output :

Random Variates : 
 [ 6.99019514  4.03402743  6.59099197  2.54849344  5.22950683  0.02399243
  0.43431935  2.38057697  8.43432847 10.53182273]

Probability Distribution : 
 [0.63655612 0.62900877 0.60973065 0.58080446 0.54500451 0.50521369
 0.46397476 0.42325628 0.38440902 0.34824122]

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 = halfcauchy .pdf(x, 1, 3)
y2 = halfcauchy .pdf(x, 1, 4)
plt.plot(x, y1, "*", x, y2, "r--")


Output :

Dominic Rubhabha-Wardslaus
Dominic Rubhabha-Wardslaushttp://wardslaus.com
infosec,malicious & dos attacks generator, boot rom exploit philanthropist , wild hacker , game developer,
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