Forecasting Process Details

Seasonal Dummy Inputs

For a seasonal cycle of length s, the seasonal dummy regressors include

\[ {\{ X_{i,t} : 1 \le i \le (s-1), 1 \le t \le n \} } \]

for models that include an intercept term and

\[ {\{ X_{i,t} : 1 \le i \le s, 1 \le t \le n \} } \]

for models that exclude an intercept term. Each element of a seasonal dummy regressor is either zero or one, based on the following rule:

\[ X_{i,t} = \begin{cases} 1,& $when $ i = t \mod {s} \\ 0,& $otherwise$ \end{cases} \]

Note that if the model includes an intercept term, the number of seasonal dummy regressors is one less than s to ensure that the linear system is full rank.

The seasonal dummy variables are included in the output data set with variable names prefixed with "SDUMMYi" and sequentially numbered. They are reserved variable names.