sympy.stats.BetaPrime() in Python
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 ) |
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 ) |
Output :
3
z
—————-
9
(z + 1) *B(4, 5)
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