In a stationary forecasting model, the value of the time series for a specific period equals the unchanging mean value of the time series plus a random error term for that period.

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In a stationary forecasting model, the time series is assumed to fluctuate around a constant mean, and any observed changes are attributed to random error, making the statement true.

In a Stationary Forecasting Model, the Value of the Time