scipy stats.bradford () | python



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: bradford continuous random variable

Code # 1: Generating a continuous random variable Bradford

# scipy import

from scipy.stats import bradford

 

numargs = bradford.numargs

[a] = [ 0.6 ,] * numargs

rv = bradford (a)

  

print ( " RV: " , rv)

Output:

 RV: & lt; scipy.stats._distn_infrastructure.rv_frozen object at 0x00000294853B04A8 & gt; 

Code # 2: Bradford random variables and probability distribution

import numpy as np

quantile = np.arange ( 0.01 , 1 , 0.1 )

 
# Random Variants

R = bradford.rvs (a, scale = 2 , size = 10 )

prin t ( "Random Variates:" , R)

 
# PDF

R = bradford.pdf (quantile, a, loc = 0 , scale = 1 )

print ( "Probability Distribution:" , R)

Output:

 Random Variates: [0.30727583 0.22129839 0.27130072 0.19795865 1.66069665 1.93938843 0.43435698 0.16437308 0.91592562 1.95369029 ] Probability Distribution: [1.26897205 1.19754774 1.13373525 1.07637933 1.02454726 0.97747771 0.93454311 0.8952215 2 0.85907529 0.82573473] 

Code # 3: Graphic representation.

import numpy as np

import matplotlib.pyplot as plt

 

distribution = np.linspace ( 0 , np.maximum (rv.dist.b , 5 ))

print ( "Distribution:" , distribution)

 

plot = plt.plot (distribution, rv.pdf (distrib ution))

Output:

 Distribution: [0. 0.10204082 0.20408163 0.30612245 0.40816327 0.51020408 0.6122449 0.71428571 0.81632653 0.91836735 1.02040816 1.12244898 1.2244898 1.32653061 1.42857143 1.53061224 1.63265306 1.73469388 1.83673469 1.93877551 2.04081633 2.14285714 2.24489796 2.34693878 2.44897959 2.55102041 2.65306122 2.75510204 2.85714286 2.95918367 3.06122449 3.16326531 3.26530612 3.36734694 3.46938776 3.57142857 3.67346939 3.7755102 3.87755102 3.97959184 4.08163265 4.18367347 4.28571429 4.3877551 4.48979592 4.59183673 4.69387755 4.79591837 4.89795918 5. ]