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Extra info for A Review of Marketing Mix: 4Ps or More?
The two exceptions are weighed by 1/(2 . f). As before, we fit next a linear model to these seasonally adjusted data to get the initial estimates for S0 and T0. The initial seasonal parameters sk0 are then computed by referencing, either additively or multiplicatively, the deseasonalized data to the corresponding actual time series observations. The results of this referencing process are averaged over all present seasons and then normalized to sum to 0 (additive seasonality) or f (multiplicative seasonality) to finally lead to the seasonal parameters sk0.
In this context, we first provide evidence for why forecasting, or, even better, superior forecasting, is a sought-after capability that many organizations invest significant resources to acquire. The recent experience of companies such as Continental Airlines Cargo or Procter & Gamble, to name a few, is illustrative of the efforts and the gains that accompany the ambition to forecast better.
5, 10, T) and j is an integer between 1 and m. 30—or estimated from the data such that the in-sample mean squared error is minimized. 50 typically reflects that either a trend, seasonal patterns or both are present in the data. If α is computed from the available time series data, the initial value S0 for the smoothed mean may impact the quality of the α estimate. Specifically, the approach that requires S0 to be the mean of the first m observations leads at times to numerical instabilities in the presence, for example, of even moderate trends in the time series data.