With the help of sympy.stats.BetaPrime() method, we can get the continuous random variable which represents the betaprime distribution.
Syntax :
sympy.stats.BetaPrime(name, alpha, beta)
Return : Return the continuous random variable.
Example #1 :
In this example we can see that by using sympy.stats.BetaPrime() method, we are able to get the continuous random variable representing the betaprime distribution by using this method.
# Import sympy and betaprime from sympy.stats import BetaPrime, density
from sympy import Symbol, pprint
alpha = Symbol("alpha", positive = True)
beta = Symbol("beta", positive = True)
z = Symbol("z")
# Using sympy.stats.BetaPrime() method X = BetaPrime("x", alpha, beta)
gfg = density(X)(z)
pprint(gfg, use_unicode = False)
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Output :
alpha – 1 -alpha – beta
z *(z + 1)
——————————-
B(alpha, beta)
Example #2 :
# Import sympy and betaprime from sympy.stats import BetaPrime, density
from sympy import Symbol, pprint
alpha = 4
beta = 5
z = Symbol("z")
# Using sympy.stats.BetaPrime() method X = BetaPrime("x", alpha, beta)
gfg = density(X)(z)
pprint(gfg, use_unicode = False)
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Output :
3
z
—————-
9
(z + 1) *B(4, 5)