sympy.stats.PowerFunction() in Python

With the help of sympy.stats.PowerFunction() method, we can get the continuous random variable which represents the Power Function distribution.

Syntax : sympy.stats.PowerFunction(name, alpha, a, b) Where, a, b and alpha are real number. Return : Return the continuous random variable.

Example #1 : In this example we can see that by using sympy.stats.PowerFunction() method, we are able to get the continuous random variable representing power function distribution by using this method. Python3 1=1

# Import sympy and PowerFunction
from sympy.stats import PowerFunction, density
from sympy import Symbol, pprint

z = Symbol("z")
alpha = Symbol("alpha", positive = True)
a = Symbol("a", positive = True)
b = Symbol("b", positive = True)

# Using sympy.stats.PowerFunction() method
X = PowerFunction("x", alpha, a, b)
gfg = density(X)(z)

print(gfg)

Output :

(-2*a + 2*z)/(-a + b)**2

Example #2 : Python3 1=1

# Import sympy and PowerFunction
from sympy.stats import PowerFunction, density, variance
from sympy import Symbol, pprint

z = Symbol("z")
alpha = 2
a = 0
b = 1

# Using sympy.stats.PowerFunction() method
X = PowerFunction("x", alpha, a, b)
gfg = density(X)(z)

pprint(variance(gfg))

Output :

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