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# 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’).

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: "scipy.stats._distn_infrastructure.rv_frozen object at 0x00000294853B04A8" `

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. ] `

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