scipy.stats.invgauss() is an inverted gauss 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 :
a : shape parameter
c : special case of gengauss. Default equals to c = -1
Code #1 : Creating Inverse Gaussian continuous random variable
# importing library from scipy.stats import invgauss numargs = invgauss.numargs [a, b] = [ 0.7 , 0.4 ] * numargs rv = invgauss (a, b) print ( "RV : \n" , rv) |
Output :
RV : scipy.stats._distn_infrastructure.rv_frozen object at 0x1a220d7bd0
Code #2 : Inverse Gaussian continuous variates and probability distribution
import numpy as np quantile = np.arange ( 0.01 , 1 ) # Random Variates R = invgauss.ppf( 0.01 , a) print ( "Random Variates : \n" , R) # PDF R = invgauss.pdf(invgauss.ppf( 0.01 , a), a) print ( "\nProbability Distribution : \n" , R) |
Output :
Random Variates : 0.25801533159920903 Probability Distribution : 0.15984442779701688
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 = invgauss .pdf(x, 1 , 3 ) y2 = invgauss .pdf(x, 1 , 4 ) plt.plot(x, y1, "*" , x, y2, "r--" ) |
Output :