With the help of sympy.stats.MultivariateBeta() method, we can create a continuous random variable with Dirichlet/Multivariate Beta Distribution.
It is a multivariate generalization of the beta distribution.
Syntax: sympy.stats.MultivariateBeta(syms, alpha) Parameters: syms: the symbol alpha: positive real numbers signifying concentration numbers Returns: a continuous random variable with multivariate beta distribution.
Example #1 :
Python3
# import sympy, MultivariateBeta, density, Symbol from sympy.stats.joint_rv_types import MultivariateBeta from sympy.stats import density from sympy import Symbol, pprint   a = Symbol('a', positive = True) b = Symbol('b', positive = True) x = Symbol('x') y = Symbol('y')   # using sympy.stats.MultivariateBeta() method M = MultivariateBeta('M', [a, b]) mvbDist = density(M)(x, y)   pprint(mvbDist) |
Output :
a1 - 1 a2 - 1
x *y *Gamma(a1 + a2)
------------------------------
Gamma(a1)*Gamma(a2)
Example #2 :
Python3
# import sympy, MultivariateBeta, density, Symbol from sympy.stats.joint_rv_types import MultivariateBeta from sympy.stats import density from sympy import Symbol, pprint   x = Symbol('x') y = Symbol('y')   # using sympy.stats.MultivariateBeta() method M = MultivariateBeta('M', [2, 1 / 2]) mvbDist = density(M)(x, y)   pprint(mvbDist) |
Output :
3*x
-------
___
4*\/ y
