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# scipy stats.genextreme () | python

scipy.stats.genextreme () — generalized continuous random variable of extreme value, which is defined by a standard format and some form 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.
-" a, b, c: shape parameters
-" moments: [optional] composed of letters [’mvsk’]; ’m’ = mean, ’v’ = variance,
’s’ = Fisher’s skew and ’k’ = Fisher’s kurtosis. (default = ’mv’).

Results: generalized extreme value continuous random variable

for == 0

for x "= 1 / a, and" 0

Code # 1: Generate a generalized extreme continuous random variable

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

Output:

RV: "scipy. stats._distn_infrastructure.rv_frozen object at 0x000001E399AB5A58"

Code # 2: generalized random values ​​of extreme values.

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

Output:

Random Variates: [1.0976659 -4.30499477 -1.30818332 1.54664658 1.44268486 1.80027137 1.52868675 1.8569798 1.36066713 - 1.85945751] Probability Distribution: [0.30397758 0.32272193 0.34399063 0.3683456 0.39653387 0.42957283 0.46888883 0.516553 45 0.57571147 0.65141728]

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 (distrib ution))

Output:

Distribution: [0. 0.02915452 0.05830904 0.08746356 0.11661808 0.14577259 0.17492711 0.20408163 0.23323615 0.26239067 0.29154519 0.32069971 0.34985423 0.37900875 0.40816327 0.43731778 0.4664723 0.49562682 0.52478134 0.55393586 0.58309038 0.6122449 0.64139942 0.67055394 0.69970845 0.72886297 0.75801749 0.78717201 0.81632653 0.84548105 0.87463557 0.90379009 0.93294461 0.96209913 0.99125364 1.02040816 1.04956268 1.0787172 1.10787172 1.13702624 1.16618076 1.19533528 1.2244898 1.25364431 1.28279883 1.31195335 1.34110787 1.37026239 1.39941691 1.42857143]

Code # 4: Various Positional Arguments

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

Exit:

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