Error Variance from Psi Weights

Problem

Compute the variance of a forecast error from the psi weights of a linear time series model. Given psi coefficients and an innovation variance sigma2, the h-step error variance is sigma2 times the sum of squared psi weights.

An empty psi list gives a variance of 0.0.

Hint

The first psi weight is always 1, contributing the current innovation variance.

Test cases

case 1

in: [[1,0.5],2]

expected: 2.5

case 2

in: [[],1]

expected: 0

case 3

in: [[1],0.5]

expected: 0.5

case 4

in: [[1,-0.5,0.25],4]

expected: 5.25

case 5

in: [[0,0],3]

expected: 0

Starter codePython

def error_variance_from_psi(psi, sigma2):
    # Your code here
    pass

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