scipy.stats.exponweib() is an exponential Weibull 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
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 : exponential Weibull continuous random variable
Code #1 : Creating exponential Weibull continuous random variable
from scipy.stats import exponweib numargs = exponweib .numargs [a, b] = [0.6, ] * numargs rv = exponweib (a, b) print ("RV : \n", rv) |
Output :
RV : <scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D5660E1D0>
Code #2 : exponential Weibull random variates and probability distribution.
import numpy as np quantile = np.arange (0.01, 1, 0.1) # Random Variates R = exponweib .rvs(a, b, scale = 2, size = 10) print ("Random Variates : \n", R) # PDF R = exponweib .pdf(a, b, quantile, loc = 0, scale = 1) print ("\nProbability Distribution : \n", R) |
Output :
Random Variates : [8.17460511e+00 1.33286202e+00 1.77493153e+01 1.83861272e-01 5.32255458e-01 1.34520149e+00 1.91022498e-02 3.08216056e-03 6.46223522e-03 1.75786657e-01] Probability Distribution : [0.00442484 0.04919014 0.09470438 0.14070318 0.1869346 0.2331608 0.27915913 0.32472306 0.36966267 0.41380492]
Code #3 : Graphical Representation.
import numpy as np import matplotlib.pyplot as plt distribution = np.linspace(0, np.minimum(rv.dist.b, 5)) print("Distribution : \n", distribution) plot = plt.plot(distribution, rv.pdf(distribution)) |
Output :
Distribution : [0. 0.10204082 0.20408163 0.30612245 0.40816327 0.51020408 0.6122449 0.71428571 0.81632653 0.91836735 1.02040816 1.12244898 1.2244898 1.32653061 1.42857143 1.53061224 1.63265306 1.73469388 1.83673469 1.93877551 2.04081633 2.14285714 2.24489796 2.34693878 2.44897959 2.55102041 2.65306122 2.75510204 2.85714286 2.95918367 3.06122449 3.16326531 3.26530612 3.36734694 3.46938776 3.57142857 3.67346939 3.7755102 3.87755102 3.97959184 4.08163265 4.18367347 4.28571429 4.3877551 4.48979592 4.59183673 4.69387755 4.79591837 4.89795918 5. ]
Code #4 : Varying Positional Arguments
import matplotlib.pyplot as plt import numpy as np x = np.linspace(0, 5, 100) # Varying positional arguments y1 = exponweib .pdf(x, 2, 6) y2 = exponweib .pdf(x, 1, 4) plt.plot(x, y1, "*", x, y2, "r--") |
Output :
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