sympy.stats.Rayleigh() in Python

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.

# 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 :

# 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 :

1/18

sympy.stats.Rayleigh() in Python

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