scipy stats.genextreme () | python

NumPy | Python Methods and Functions

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:
- & gt; q: lower and upper tail probability
- & 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; a, b, c: shape parameters
- & gt; 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 & lt; = 1 / a, and & gt; 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: & lt; scipy. stats._distn_infrastructure.rv_frozen object at 0x000001E399AB5A58 & gt;

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:

scipy stats.genextreme () | python

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