Models

Two different modeling approaches are available; multiplicative or additive.

• Multiplicative. The seasonal component is a factor by which the seasonally adjusted series is multiplied to yield the original series. In effect, seasonal components that are proportional to the overall level of the series. Observations without seasonal variation have a seasonal component of 1.
• Additive. The seasonal adjustments are added to the seasonally adjusted series to obtain the observed values. This adjustment attempts to remove the seasonal effect from a series in order to look at other characteristics of interest that may be "masked" by the seasonal component. In effect, seasonal components that do not depend on the overall level of the series. Observations without seasonal variation have a seasonal component of 0.

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