Importance Sampling Weights

Problem

Importance sampling corrects samples drawn from proposal to the target distribution by the ratio target[i] / proposal[i]. Return the list of importance weights for equal-length vectors, or an empty list when the inputs are empty, mismatched, or any proposal probability is nonpositive.

Hint

A weight above 1 means the target assigns more mass than the proposal there.

Test cases

case 1

in: [[0.5,0.5],[0.5,0.5]]

expected: [1,1]

case 2

in: [[0.2,0.8],[0.5,0.5]]

expected: [0.4,1.6]

case 3

in: [[0.1,0.9],[0.25,0.75]]

expected: [0.4,1.2]

case 4

in: [[],[]]

expected: []

case 5

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

expected: []

Starter codePython

def importance_sampling_weights(target, proposal):
    # Your code here
    pass

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