Beta Conjugate Update Parameters

Problem

A Beta(alpha, beta) prior is conjugate for the binomial likelihood, so after successes successes in trials trials the posterior is Beta(alpha + successes, beta + trials - successes). Return the updated parameters as [alpha_new, beta_new], or [0.0, 0.0] for invalid arguments.

Hint

The update simply adds successes to alpha and failures to beta.

Test cases

case 1

in: [1,1,3,10]

expected: [4,8]

case 2

in: [2,5,4,6]

expected: [6,7]

case 3

in: [1,1,0,0]

expected: [1,1]

case 4

in: [2,2,6,6]

expected: [8,2]

case 5

in: [1,1,-1,3]

expected: [0,0]

Starter codePython

def beta_conjugate_update(alpha, beta, successes, trials):
    # Your code here
    pass

5 test cases · run your code against them in the editor