Exponentially Weighted Mean

Problem

Return the final exponentially weighted mean with smoothing factor alpha: y_0 = data[0] and y_t = alpha*x_t + (1-alpha)*y_(t-1). Return 0.0 for empty input.

Hint

Loop once, updating y from the previous value.

Test cases

case 1

in: [[1,2,3,4,5],0.5]

expected: 4.0625

case 2

in: [[10,20,30],0.5]

expected: 22.5

case 3

in: [[5],0.3]

expected: 5

case 4

in: [[],0.5]

expected: 0

case 5

in: [[1,1,1],0.9]

expected: 1

Starter codePython

def ewma(data, alpha):
    # Your code here
    pass

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