Gamma-Poisson Posterior Parameters

Problem

A Gamma(alpha, beta) prior on a Poisson rate is updated with a list of observed counts. The conjugate posterior is Gamma(alpha + sum(counts), beta + len(counts)). Return the posterior parameters as [shape, rate], or [0.0, 0.0] when alpha or beta is nonpositive or any count is negative.

Hint

Counts add to the shape and each observation adds one to the rate.

Test cases

case 1

in: [2,1,[3,4,5]]

expected: [14,4]

case 2

in: [0.5,0.5,[]]

expected: [0.5,0.5]

case 3

in: [1,2,[0,0]]

expected: [1,4]

case 4

in: [3,1,[2]]

expected: [5,2]

case 5

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

expected: [0,0]

Starter codePython

def gamma_poisson_posterior_parameters(alpha, beta, counts):
    # Your code here
    pass

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