scipy.stats.johnsonsu() is a Johnson SU 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 : Johnson SU continuous random variable
Code #1 : Creating Johnson SU continuous random variable
# importing library from scipy.stats import johnsonsu numargs = johnsonsu.numargs a, b = 4.32, 3.18rv = johnsonsu(a, b) print ("RV : \n", rv) |
Output :
RV : scipy.stats._distn_infrastructure.rv_frozen object at 0x000002A9D4E91708
Code #2 : Johnson SU continuous variates and probability distribution
import numpy as np quantile = np.arange (0.01, 1, 0.1) # Random Variates R = johnsonsu.rvs(a, b, scale = 2, size = 10) print ("Random Variates : \n", R) # PDF R = johnsonsu.pdf(a, b, quantile, loc = 0, scale = 1) print ("\nProbability Distribution : \n", R) |
Output :
Random Variates : [-6.33841843 -5.35469028 -5.36145351 -4.4504208 -1.91574847 -5.01633416 -5.37699657 -4.15794134 -4.90450547 -2.93846617] Probability Distribution : [5.34745702e-06 2.86846536e-05 2.54767528e-05 1.66921608e-05 9.34800722e-06 4.69729578e-06 2.16525150e-06 9.26607636e-07 3.70800055e-07 1.39402846e-07]
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 = johnsonsu .pdf(x, 1, 3) y2 = johnsonsu .pdf(x, 1, 4) plt.plot(x, y1, "*", x, y2, "r--") |
Output :
