With the help of sympy.stats.Kumaraswamy()
method, we can get the continuous random variable which represents the kumaraswamy distribution.
Syntax :
sympy.stats.Kumaraswamy(name, a, b)
Where, a and b are real number and a, b > 0.
Return : Return the continuous random variable.
Example #1 :
In this example we can see that by using sympy.stats.Kumaraswamy()
method, we are able to get the continuous random variable representing kumaraswamy distribution by using this method.
# Import sympy and Kumaraswamy from sympy.stats import Kumaraswamy, density
from sympy import Symbol, pprint
z = Symbol( "z" )
a = Symbol( "a" , positive = True )
b = Symbol( "b" , positive = True )
# Using sympy.stats.Kumaraswamy() method X = Kumaraswamy( "x" , a, b)
gfg = density(X)(z)
pprint(gfg) |
Output :
b – 1
a – 1 / a\
a*b*z *\1 – z /
Example #2 :
# Import sympy and Kumaraswamy from sympy.stats import Kumaraswamy, density
from sympy import Symbol, pprint
z = 0.3
a = 2
b = 6
# Using sympy.stats.Kumaraswamy() method X = Kumaraswamy( "x" , a, b)
gfg = density(X)(z)
pprint(gfg) |
Output :
2.24651572236000