249. M-Md-M

Fully multiplicative with damped trend

ETS(𝑀,Md,𝑀)𝑥𝑡=𝑙𝑡1𝑏𝑡1𝜑𝑠𝑡𝑚(1+𝜀𝑡)𝑙𝑡=𝑙𝑡1𝑏𝑡1𝜑(1+𝛼𝜀𝑡)𝑏𝑡=𝑏𝑡1𝜑(1+𝛽𝜀𝑡)𝑠𝑡=𝑠𝑡𝑚(1+𝛾𝜀𝑡)𝑥̂𝑡+|𝑡=𝑙𝑡𝑏𝑡𝜑+𝜑2++𝜑𝑠𝑡+𝑚+
Example: ETS(𝑀,Md,𝑀)

Given

  • Smoothing parameters: 𝛼=0.5, 𝛽=0.4, 𝜑=0.8, 𝛾=0.2
  • Initial states: 𝑙0=12, 𝑏0=1, (𝑠3,𝑠2,𝑠1,𝑠0)=(1.2,1,0.8,1), seasonal period 𝑚=4
  • Data:
𝑡12345678910111213141516
x𝑡121081114129131614111518161317

Step 1 — formula

Observation:

𝑥𝑡=(𝑙𝑡1𝑏𝑡1𝜑𝑠𝑡𝑚)(1+𝜀𝑡)

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

𝜇𝑡=𝑙𝑡1𝑏𝑡1𝜑𝑠𝑡𝑚

Innovation:

𝜀𝑡=(𝑥𝑡𝜇𝑡)/𝜇𝑡

State updates:

𝑙𝑡=𝑙𝑡1𝑏𝑡1𝜑(1+𝛼𝜀𝑡)𝑏𝑡=𝑏𝑡1𝜑(1+𝛽𝜀𝑡)𝑠𝑡=𝑠𝑡𝑚(1+𝛾𝜀𝑡)

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

𝑥̂𝑡+|𝑡=𝑙𝑡𝑏𝑡𝜑+𝜑2++𝜑𝑠𝑡+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=1210.81.2=14.4𝜀1=(𝑥1𝜇1)/𝜇1=(1214.4)/14.4=0.1667𝑙1=1210.8(1+0.5(0.1667))=11𝑏1=10.8(1+0.4(0.1667))=0.9333𝑠1=1.2(1+0.2(0.1667))=1.16

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=𝑙𝑡1𝑏𝑡1𝜑𝑠𝑡𝑚𝜀𝑡𝑙𝑡=𝑙𝑡1𝑏𝑡1𝜑(1+𝛼𝜀𝑡)𝑏𝑡=𝑏𝑡1𝜑(1+𝛽𝜀𝑡)𝑠𝑡=𝑠𝑡𝑚(1+𝛾𝜀𝑡)
11214.40.1667110.93331.16
21010.40930.039310.20470.93140.9921
387.71270.03739.82040.95880.806
4119.49560.158410.24781.02821.0317
51412.15490.151811.27371.08461.1952
61211.93570.005412.06271.06940.9932
7910.25830.122711.94741.00340.7862
81312.35940.051812.29021.02351.0424
91614.9650.069212.95371.04691.2118
101413.34660.04913.76681.05771.0029
111111.320.028314.19511.03410.7817
121515.19860.013114.48541.02181.0397
131817.8580.00814.7961.02061.2137
141615.08370.060715.49651.04121.0151
151312.51160.03916.31711.04890.7878
161717.62510.035516.65211.02421.0323