With the help of sympy.stats.Multinomial() method, we can create a discrete random variable with Multinomial Distribution.
A multinomial distribution is the probability distribution of the outcomes from a multinomial experiment.
Syntax: sympy.stats.Multinomial(syms, n, p) Parameters: syms: the symbol n: is the number of trials, a positive integer p: event probabilites, p>= 0 and p<= 1 Returns: a discrete random variable with Multinomial Distribution
Example #1 :
Python3
# import sympy, Multinomial, density, symbols from sympy.stats.joint_rv_types import Multinomial from sympy.stats import density from sympy import symbols, pprint   x1, x2, x3 = symbols('x1, x2, x3', nonnegative = True, integer = True) p1, p2, p3 = symbols('p1, p2, p3', positive = True)   # Using sympy.stats.Multinomial() method M = Multinomial('M', 3, p1, p2, p3) multiDist = density(M)(x1, x2, x3)   pprint(multiDist) |
Output :
/ x1 x2 x3 |6*p1 *p2 *p3 |---------------- for x1 + x2 + x3 = 3 < x1!*x2!*x3! | | 0 otherwise \
Example #2 :
Python3
# import sympy, Multinomial, density, symbols from sympy.stats.joint_rv_types import Multinomial from sympy.stats import density from sympy import symbols, pprint   x1, x2, x3 = symbols('x1, x2, x3', nonnegative = True, integer = True)   # Using sympy.stats.Multinomial() method M = Multinomial('M', 4, 0, 1, 0) multiDist = density(M)(x1, x2, x3)   pprint(multiDist) |
Output :
/ x1 x3 | 24*0 *0 |----------- for x1 + x2 + x3 = 4 <x1!*x2!*x3! | | 0 otherwise \
