Exercise
A time series was observed at times 0, 1, …, 100. The last four observations along with estimates based on exponential and double exponential smoothing with [math]w = 0.8[/math] are:
Time (t) | 97 | 98 | 99 | 100 |
---|---|---|---|---|
Observation ( [math]y_t[/math] ) | 96.9 | 98.1 | 99.0 | 100.2 |
Estimates ( [math]\hat{s_1}(t) [/math] | 93.1 | 94.1 | 95.1 | |
Estimates ( [math]\hat{s_2}(t)[/math] | 88.9 | 89.9 |
All forecasts should be rounded to one decimal place and the trend should be rounded to three decimal places.
Let [math]F[/math] be the predicted value of [math]y_{102}[/math] using exponential smoothing with [math]w = 0.8.[/math]
Let [math]G[/math] be the predicted value of [math]y_{102}[/math] using double exponential smoothing with [math]w = 0.8.[/math]
Calculate the absolute difference between [math]F[/math] and [math]G[/math], [math]| F − G |[/math] .
- 0.0
- 2.1
- 4.2
- 6.3
- 8.4
Key: D
The smoothed forecast at 100 is
0.2(100.2) + 0.8(95.1) = 96.1.
This is also the forecast at 102. The smoothed values are at 99:
0.2(95.1) + 0.8(89.9) = 90.9. At 100: 0.2(96.1) + 0.8(90.9) = 91.9.
The trend is
0.2(96.1 – 91.9)/.8 = 1.05.
The intercept (value at 100) is
2(96.1) – 91.9 = 100.3.
The forecast at time 102 is
100.3 + 2(1.05) = 102.4.
The difference is 6.3.