scipy stats.gamma() | Python (original) (raw)

Last Updated : 27 Mar, 2019

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

Python3 `

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.

Python3 `

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.

Python3 `

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

Python3 `

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 :