ml_products.py

import math
import numpy as np

def f(n):
  return math.factorial(n)

def mle(R, theta):
  return (f(np.sum(R)) / (np.prod([f(r) for r in R]))) * \
         np.prod([theta[i]**R[i] for i in range(len(R))])

# maximum likelihood
ml_A = mle(R_A,theta_A)
ml_B = mle(R_B,theta_B)

print("ML for Product A {:.7f}".format(ml_A))
print("ML for Product B {:.7f}".format(ml_B))