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scipy stats.gamma() | Python

Last Updated : 27 Mar, 2019
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scipy.stats.gamma() is an gamma 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.
-> a : shape parameters
-> moments : [optional] composed of letters [‘mvsk’]; ‘m’ = mean, ‘v’ = variance, ‘s’ = Fisher’s skew and ‘k’ = Fisher’s kurtosis. (default = ‘mv’).

Results : gamma continuous random variable

Code #1 : Creating gamma continuous random variable




from scipy.stats import gamma 
  
numargs = gamma .numargs
[a] = [0.7, ] * numargs
rv = gamma (a)
  
print ("RV : \n", rv) 


Output :

RV : 
 <scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D57997F60>

Code #2 : generalized gamma random variates.




import numpy as np
quantile = np.arange (0.01, 1, 0.1)
   
# Random Variates
R = gamma.rvs(a, scale = 2,  size = 10)
print ("Random Variates : \n", R)
  
# PDF
R = gamma.pdf(a, quantile, loc = 0, scale = 1)
print ("\nProbability Distribution : \n", R)


Output :

Random Variates : 
 [0.01601209 0.05164555 1.22072489 0.53476245 0.11529018 0.16966403
 0.59198231 0.71995529 0.86063603 3.81492177]

Probability Distribution : 
 [0.00710916 0.07919869 0.15097014 0.21974949 0.28337498 0.34020629
 0.38910556 0.42939763 0.46081639 0.48344302]

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 = gamma.pdf(x, a, 1, 3)
y2 = gamma.pdf(x, a, 1, 4)
plt.plot(x, y1, "*", x, y2, "r--")


Output :



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