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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.




# Import sympy and LogLogistic
from sympy.stats import LogLogistic, density
from sympy import Symbol, pprint
  
z = Symbol("z")
alpha = Symbol("alpha", positive = True)
beta = Symbol("beta", positive = True)
  
# Using sympy.stats.LogLogistic() method
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 :




# Import sympy and LogLogistic
from sympy.stats import LogLogistic, density
from sympy import Symbol, pprint
  
z = 1.2
alpha = 2
beta = 3
  
# Using sympy.stats.LogLogistic() method
X = LogLogistic("x", alpha, beta)
gfg = density(X)(z)
  
pprint(gfg)

Output :

0.365196502770083

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