scipy.stats.genpareto() is an generalized Pareto 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, b : 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 [‘mvsk’]; ‘m’ = mean, ‘v’ = variance, ‘s’ = Fisher’s skew and ‘k’ = Fisher’s kurtosis. (default = ‘mv’).Results : generalized Pareto continuous random variable
Code #1 : Creating generalized Pareto continuous random variable
from scipy.stats import genpareto   numargs = genpareto .numargs [a] = [0.7, ] * numargs rv = genpareto (a)   print ("RV : \n", rv) |
Output :
RV : <scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D579B85C0>
Code #2 : generalized Pareto random variates.
import numpy as np quantile = np.arange (0.01, 1, 0.1)    # Random Variates R = genpareto.rvs(a, scale = 2, size = 10) print ("Random Variates : \n", R) |
Output :
Random Variates : [ 1.55978773 0.03897083 7.68148511 0.78339525 1.1217962 0.20434352 1.16663003 2.06115353 12.82886098 0.27780119]
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 = genpareto.pdf(x, 1, 3) y2 = genpareto.pdf(x, 1, 4) plt.plot(x, y1, "*", x, y2, "r--") |
Output :
