sympy.stats.PowerFunction() in Python
Last Updated :
08 Jun, 2020
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.
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 )
X = PowerFunction( "x" , alpha, a, b)
gfg = density(X)(z)
print (gfg)
|
Output :
(-2*a + 2*z)/(-a + b)**2
Example #2 :
from sympy.stats import PowerFunction, density, variance
from sympy import Symbol, pprint
z = Symbol( "z" )
alpha = 2
a = 0
b = 1
X = PowerFunction( "x" , alpha, a, b)
gfg = density(X)(z)
pprint(variance(gfg))
|
Output :
1/18
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