224. A-A-A

Additive Holt-Winters

ETS(𝐴,𝐴,𝐴)𝑥𝑡=𝑙𝑡1+𝑏𝑡1+𝑠𝑡𝑚+𝜀𝑡𝑙𝑡=𝑙𝑡1+𝑏𝑡1+𝛼𝜀𝑡𝑏𝑡=𝑏𝑡1+𝛽𝜀𝑡𝑠𝑡=𝑠𝑡𝑚+𝛾𝜀𝑡𝑥̂𝑡+|𝑡=𝑙𝑡+𝑏𝑡+𝑠𝑡+𝑚+
Example: ETS(𝐴,𝐴,𝐴)

Given

  • Smoothing parameters: 𝛼=0.5, 𝛽=0.4, 𝛾=0.2
  • Initial states: 𝑙0=12, 𝑏0=0.5, (𝑠3,𝑠2,𝑠1,𝑠0)=(2,0,3,1), seasonal period 𝑚=4
  • Data:
𝑡12345678910111213141516
x𝑡121081114129131614111518161317

Step 1 — formula

Observation:

𝑥𝑡=𝑙𝑡1+𝑏𝑡1+𝑠𝑡𝑚+𝜀𝑡

Conditional mean (one-step-ahead forecast 𝑥̂𝑡|𝑡1=𝜇𝑡):

𝜇𝑡=𝑙𝑡1+𝑏𝑡1+𝑠𝑡𝑚

Innovation:

𝜀𝑡=𝑥𝑡𝜇𝑡

State updates:

𝑙𝑡=𝑙𝑡1+𝑏𝑡1+𝛼𝜀𝑡𝑏𝑡=𝑏𝑡1+𝛽𝜀𝑡𝑠𝑡=𝑠𝑡𝑚+𝛾𝜀𝑡

Forecast steps ahead from time 𝑡 (using current-period states):

𝑥̂𝑡+|𝑡=𝑙𝑡+𝑏𝑡+𝑠𝑡+𝑚+

where {1,2,3,} is the forecast horizon (how many steps ahead); 𝑚+=((1)mod𝑚)+1 picks the right seasonal slot for the period steps ahead (cycles through 1,2,,𝑚).

Step 2 — apply at 𝑡=1

𝜇1=12+0.5+2=14.5𝜀1=𝑥1𝜇1=1214.5=2.5𝑙1=12+0.5+0.5(2.5)=11.25𝑏1=0.5+0.4(2.5)=0.5𝑠1=2+0.2(2.5)=1.5

Step 3 — iterate

Each column header is the equation that produced its values. Values rounded to 4 decimal places; arithmetic performed at full precision.

𝑡𝑥𝑡𝜇𝑡=𝑙𝑡1+𝑏𝑡1+𝑠𝑡𝑚𝜀𝑡𝑙𝑡=𝑙𝑡1+𝑏𝑡1+𝛼𝜀𝑡𝑏𝑡=𝑏𝑡1+𝛽𝜀𝑡𝑠𝑡=𝑠𝑡𝑚+𝛾𝜀𝑡
11214.52.511.250.51.5
21010.750.7510.3750.80.15
386.5751.42510.28750.232.715
41111.05750.057510.02870.2530.9885
51411.27572.724311.13790.83672.0449
61211.82460.175412.06230.90690.1149
7910.25421.254212.34210.40522.9658
81313.73580.735812.37940.11090.8413
91614.53511.464913.22270.69682.3378
101413.80460.195414.01720.7750.0758
111111.82640.826414.3790.44443.1311
121515.66480.664814.49110.17850.7084
131817.00740.992615.16590.57562.5363
141615.66560.334415.90860.70930.009
151313.48680.486816.37450.51463.2285
161717.59750.597516.59040.27560.5889