sympy.stats.LogLogistic() in python
Last Updated :
05 Jun, 2020
With the help of sympy.stats.LogLogistic()
method, we can get the continuous random variable which represents the Log-Logistic distribution.
Syntax : sympy.stats.LogLogistic(name, alpha, beta)
Where, alpha and beta are real number and alpha, beta > 0.
Return : Return the continuous random variable.
Example #1 :
In this example we can see that by using sympy.stats.LogLogistic()
method, we are able to get the continuous random variable representing Log-Logistic distribution by using this method.
from sympy.stats import LogLogistic, density
from sympy import Symbol, pprint
z = Symbol( "z" )
alpha = Symbol( "alpha" , positive = True )
beta = Symbol( "beta" , positive = True )
X = LogLogistic( "x" , alpha, beta)
gfg = density(X)(z)
pprint(gfg)
|
Output :
beta – 1
/ z \
beta*|—–|
\alpha/
————————
2
/ beta \
|/ z \ |
alpha*||—–| + 1|
\\alpha/ /
Example #2 :
from sympy.stats import LogLogistic, density
from sympy import Symbol, pprint
z = 1.2
alpha = 2
beta = 3
X = LogLogistic( "x" , alpha, beta)
gfg = density(X)(z)
pprint(gfg)
|
Output :
0.365196502770083
Like Article
Suggest improvement
Share your thoughts in the comments
Please Login to comment...