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 Beninifrom sympy.stats import Benini, density, cdffrom sympy import Symbol, simplify, pprintalpha = Symbol("alpha", positive = True)beta = Symbol("beta", positive = True)sigma = Symbol("sigma", positive = True)z = Symbol("z")# Using sympy.stats.Benini() methodX = 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 Beninifrom sympy.stats import Benini, density, cdffrom sympy import Symbol, simplify, pprintalpha = 4beta = 6sigma = 3z = 0.2# Using sympy.stats.Benini() methodX = Benini("x", alpha, beta, sigma)GFG = density(X)(z)pprint(GFG, use_unicode = False) |
Output :
-5.60587100451865e-13
