Weigthed Moving Average (WMA)
For the Weigthed Moving Average (WMA) the immediate past is the most relevant in forecasting the immediate future. Weighted moving averages are used to place weight on the most recent observations. The sum of the weights must equal one.
- Suppose we have a WMA of four weights: 0.1, 0.2, 0.3 and 0.4
- Our serie has a periodicity of 'MONTH'
- Starts with January
The first forecast is then:
WMA(May) = 0.1 * Jan + 0.2 * Feb + 0.3 * Mar + 0.4 * Apr
The first forecast for weights: 0.1, 0.2, 0.3 and 0.4
Demand 1: date 2000-01-01 value is 779
Demand 2: date 2000-02-01 value is 920
Demand 3: date 2000-03-01 value is 848
Demand 4: date 2000-04-01 value is 839
F5=May = 0.1 * 779 + 0.2 * 920 + 0.3 * 848 + 0.4 * 839 = 851.9
The date for t=5 is 2000-05-01