This model is used to exclude irregularities in the time series pattern. In order to this, the average of the n last time series values is calculated. The average can always be calculated from n values according to formula (1).
Therefore, the new average is calculated from the previous average and the current consumption value weighted with 1/n, minus the oldest consumption value weighted with 1/n.
It is only worth using this procedure for time series which are constant, that is, for time series with no trend-like or season-like patterns. As all historical data is equally weighted with the factor 1/n, it takes precisely n periods until the forecast can adapt to a possible level change.
No comments:
Post a Comment