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 = 1.2alpha = 2beta = 3 # Using sympy.stats.LogLogistic() method X = LogLogistic("x", alpha, beta) gfg = density(X)(z) pprint(gfg) |
Output :
0.365196502770083
