sympy.stats.Benini() in Python

With the help of sympy.stats.Benini() method, we can get the continuous random variable representing the benini distribution.

Syntax : sympy.stats.Benini(name, alpha, beta, sigma) 
Where, alpha, beta and sigma are real number and greater than 0. 

Return : Return the continuous random variable. 

Example #1 :

In this example, we can see that by using sympy.stats.Benini() method, we are able to get the continuous random variable represents the benini distribution by using this method.

Python3

# Import sympy and Benini
from sympy.stats import Benini, density, cdf
from sympy import Symbol, simplify, pprint

alpha = Symbol("alpha", positive = True)
beta = Symbol("beta", positive = True)
sigma = Symbol("sigma", positive = True)
z = Symbol("z")

# Using sympy.stats.Benini() method
X = Benini("x", alpha, beta, sigma)
GFG = density(X)(z)

pprint(GFG, use_unicode = False)

Output :

/ / z \\ / z \ 2/ z \ 
| 2*beta*log|—–|| – alpha*log|—–| – beta*log |—–| 
|alpha \sigma/| \sigma/ \sigma/ 
|—– + —————–|*e 
\ z z / 

Example #2 :

Python3

# Import sympy and Benini
from sympy.stats import Benini, density, cdf
from sympy import Symbol, simplify, pprint

alpha = 4
beta = 6
sigma = 3
z = 0.2

# Using sympy.stats.Benini() method
X = Benini("x", alpha, beta, sigma)
GFG = density(X)(z)

pprint(GFG, use_unicode = False)

Output :

-5.60587100451865e-13