Expanding Origin Training Size

Problem

Compute the total number of training observations used across expanding-origin evaluations. Origins start with min_initial observations and grow one at a time; the last training set ends at n - horizon.

Return the sum of those training sizes, or 0 if none are valid. For example (6, 2, 1) sums sizes 2, 3, 4 and 5.

Hint

Sizes grow by one each origin, so this is a simple arithmetic series sum.

Test cases

case 1

in: [10,3,1]

expected: 42

case 2

in: [5,5,2]

expected: 0

case 3

in: [6,2,1]

expected: 14

case 4

in: [4,4,1]

expected: 0

Starter codePython

def expanding_origin_training_size(n, min_initial, horizon):
    # Your code here
    pass

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