# scipy stats.frechet_r() | Python

Last Updated : 27 Mar, 2019

scipy.stats.frechet_r() is an Frechet right (or Weibull minimum) 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
-> a : shape parameters
-> 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 [â€˜mvskâ€™]; ‘m’ = mean, ‘v’ = variance, ‘s’ = Fisher’s skew and ‘k’ = Fisher’s kurtosis. (default = ‘mv’).

Results : Frechet right continuous random variable

Code #1 : Creating Frechet right continuous random variable

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

Output :

```RV :
<scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D56769470>
```

Code #2 : Frechet right random variates and probability distribution.

 `import` `numpy as np ` `quantile ``=` `np.arange (``0.01``, ``1``, ``0.1``) ` `  `  `# Random Variates ` `R ``=` `frechet_r .rvs(a, scale ``=` `2``,  size ``=` `10``) ` `print` `(``"Random Variates : \n"``, R) ` ` `  `# PDF ` `R ``=` `frechet_r .pdf(a, quantile, loc ``=` `0``, scale ``=` `1``) ` `print` `(``"\nProbability Distribution : \n"``, 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 : 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 ``=` `frechet_r .pdf(x, ``1``, ``3``) ` `y2 ``=` `frechet_r .pdf(x, ``1``, ``4``) ` `plt.plot(x, y1, ``"*"``, x, y2, ``"r--"``) `

Output :

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