scipy.stats.frechet_l() is an Frechet left (or Weibull maximum) 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 : 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 : Frechet left continuous random variable
Code #1 : Creating Frechet left continuous random variable
from scipy.stats import frechet_l numargs = frechet_l .numargs [a] = [0.7, ] * numargs rv = frechet_l (a) print ("RV : \n", rv) |
Output :
RV : <scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D578BC9E8>
Code #2 : Frechet left random variates and probability distribution.
import numpy as np quantile = np.arange (0.01, 1, 0.1) # Random Variates R = frechet_l.rvs(a, scale = 2, size = 10) print ("Random Variates : \n", R) # PDF R = frechet_l.pdf(a, quantile, loc = 0, scale = 1) print ("\nProbability Distribution : \n", R) |
Output :
Random Variates : [-4.66775585e-02 -3.75425255e+00 -2.32248407e-01 -1.20807347e-03 -6.26373883e+00 -1.14007755e+00 -5.09499683e+00 -4.18191271e-01 -4.33720753e+00 -1.05442843e+00] Probability Distribution : [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
Code #3 : Varying Positional Arguments
import matplotlib.pyplot as plt import numpy as np x = np.linspace(0, 5, 100) # Varying positional arguments y1 = frechet_l.pdf(x, 1, 3) y2 = frechet_l.pdf(x, 1, 4) plt.plot(x, y1, "*", x, y2, "r--") |
Output :
