sympy.stats.Beta() in Python

sympy.stats.Benini() in Python

Last Updated : 18 Aug, 2021

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

sympy.stats.Beta() in Python

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