  # scipy stats.frechet_r () | python

NumPy | Python Methods and Functions

Parameters:
- & gt; q: lower and upper tail probability
- & gt; a: shape parameters
- & gt; x: quantiles
- & gt; loc: [optional] location parameter. Default = 0
- & gt; scale: [optional] scale parameter. Default = 1
- & gt; size: [tuple of ints, optional] shape or random variates.
- & gt; moments: [optional] composed of letters [`mvsk`]; `m` = mean, `v` = variance, `s` = Fisher`s skew and `k` = Fisher`s kurtosis. (default = `mv`).

Results: Frechet right continuous random variable

Code # 1: Create right continuous random variable random variable Frechet

 ` from ` ` scipy.stats ` ` import ` ` frechet_r ` ` `  ` numargs ` ` = ` ` frechet_r .numargs ` ` [a] ` ` = ` ` [` ` 0.7 ` `,] ` ` * ` ` numargs ` ` rv ` ` = ` ` frechet_r (a) `   < code class = "functions"> print ` (` ` "RV:" ` `, rv) `

Output:

` RV: & lt; scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D56769470 & gt; `

Code # 2: Frechet random right-handed variations and probability distribution.

` `

 ` import ` ` numpy as np ` ` quantile ` ` = ` ` np.arange (` ` 0.01 ` `, ` ` 1 ` `, ` ` 0.1 ` `) `   ` # Random Variants ` ` R ` ` = ` ` frechet_r .rvs (a, scale ` ` = ` ` 2 ` `, size ` ` = ` ` 10 ` `) ` ` print ` ` (` `" Random Variates: "` `, R) `   ` # PDF ` ` R ` ` = ` ` frechet_r .pdf (a, quantile, loc ` ` = ` ` 0 ` `, scale ` ` = ` ` 1 ` `) ` ` print ` ` (` ` "Probability Distribution:" ` `, R) `

Output:

` Random Variates: [0.74797562 0.45139233 3.17050565 0.83673559 0.04150534 0.04417758 0.08459631 0.58419257 4.88454049 3.68323048] Probability Distribution: [0.00525539 0.05776573 0.11006225 0.16196069 0.21328776 0.26388153 0.31359184 0 .36228041 0.40982097 0.45609917] `

Code # 3: Graphic representation.

` `

 ` import ` ` numpy as np ` ` import ` ` matplotlib.pyplot as plt ``   distribution = np.linspace ( 0 , np.minimum (rv.dist. b, 3 )) print ( "Distribution:" , 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: Various Positional Arguments

 ` import ` ` matplotlib. pyplot as plt ` ` import ` numpy as np   ` x ` ` = ` ` np.linspace (` ` 0 ` `, ` ` 5 ` `, ` ` 100 ` `) `   ` # Various positional arguments `` y1 = frechet_r .pdf (x, 1 , 3 ) y2 = frechet_r .pdf (x , 1 , 4 ) plt.plot (x, y1, " * " , x, y2, " r-- " ) `

Output: