Python – Weibull Maximum Distribution in Statistics
scipy.stats.weibull_max() is a Weibull maximum continuous random variable. It is inherited from the of generic methods as an instance of the rv_continuous class. It completes the methods with details specific for this particular distribution.
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’).
Results : Weibull maximum continuous random variable
Code #1 : Creating Weibull maximum continuous random variable
from scipy.stats import weibull_max
numargs = weibull_max .numargs
a, b = 0.2 , 0.8
rv = weibull_max (a, b)
print ( "RV : \n" , rv)
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Output :
RV :
scipy.stats._distn_infrastructure.rv_frozen object at 0x000002A9DA07FDC8
Code #2 : Weibull maximum continuous variates and probability distribution
import numpy as np
quantile = np.arange ( 0.01 , 1 , 0.1 )
R = weibull_max .rvs(a, b, size = 10 )
print ( "Random Variates : \n" , R)
x = np.linspace(weibull_max.ppf( 0.01 , a, b),
weibull_max.ppf( 0.99 , a, b), 10 )
R = weibull_max.pdf(x, 1 , 3 )
print ( "\nProbability Distribution : \n" , R)
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Output :
Random Variates :
[ 7.99998841e-01 7.96362853e-01 -1.36808367e+00 -5.04876338e-01
-8.07612996e+03 2.47694796e-01 7.80624490e-01 7.99996977e-01
7.95962734e-01 6.94775447e-01]
Probability Distribution :
[0.00000000e+000 0.00000000e+000 0.00000000e+000 0.00000000e+000
0.00000000e+000 0.00000000e+000 1.59673931e-301 1.41364401e-201
1.25154393e-101 1.10803158e-001]
Code #3 : Graphical Representation.
import numpy as np
import matplotlib.pyplot as plt
distribution = np.linspace( 0 , np.minimum(rv.dist.b, 2 ))
print ( "Distribution : \n" , distribution)
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Output :
Distribution :
[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
0. 0.]
Code #4 : Varying Positional Arguments
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace( 0 , 5 , 100 )
y1 = weibull_max.pdf(x, a, b)
y2 = weibull_max.pdf(x, a, b)
plt.plot(x, y1, "*" , x, y2, "r--" )
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Output :
Last Updated :
10 Jan, 2020
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