Given the data: 12 y(t) K K+2 K+3 K+5 K+6 K+8 3 4 5 6. a)...

 

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Given the data: 12 y(t) K K+2 K+3 K+5 K+6 K+8 3 4 5 6. a) Forecast y(1), y(2),...,y(7) using simple exponential smoothing 2 with a = 5* b) Find m, the mean of y. Let z(t) = y(t) – m. For z(t), find ACF of lag-1 (P1) and lag-2 (P2) using the formula for ACF. c) Find an AR(2) model for z(t) by finding the parameters Ø1, 02 using (P1, P2). Is the AR(2) model, stationary? Justify. Forecast y(7) using the AR(2) model. K=9 Given the data: 12 y(t) K K+2 K+3 K+5 K+6 K+8 3 4 5 6. a) Forecast y(1), y(2),...,y(7) using simple exponential smoothing 2 with a = 5* b) Find m, the mean of y. Let z(t) = y(t) – m. For z(t), find ACF of lag-1 (P1) and lag-2 (P2) using the formula for ACF. c) Find an AR(2) model for z(t) by finding the parameters Ø1, 02 using (P1, P2). Is the AR(2) model, stationary? Justify. Forecast y(7) using the AR(2) model. K=9