Friday, September 26, 2025
HomeLanguagesscipy stats.halfcauchy() | Python

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
Dominichttp://wardslaus.com
infosec,malicious & dos attacks generator, boot rom exploit philanthropist , wild hacker , game developer,
RELATED ARTICLES

Most Popular

Dominic
32321 POSTS0 COMMENTS
Milvus
84 POSTS0 COMMENTS
Nango Kala
6683 POSTS0 COMMENTS
Nicole Veronica
11854 POSTS0 COMMENTS
Nokonwaba Nkukhwana
11910 POSTS0 COMMENTS
Shaida Kate Naidoo
6795 POSTS0 COMMENTS
Ted Musemwa
7071 POSTS0 COMMENTS
Thapelo Manthata
6757 POSTS0 COMMENTS
Umr Jansen
6762 POSTS0 COMMENTS