22 lines
1,001 B
TeX
22 lines
1,001 B
TeX
\subsubsection{Vertical and Real-time Forecasts with Retraining}
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\label{rt}
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The lower-left in Figure \ref{f:inputs} shows how models trained on vertical
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time series are extended with real-time order data as it becomes available
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during a test day:
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Instead of obtaining an $H$-step-ahead forecast, we retrain a model after
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every time step and only predict one step.
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The remainder is as in the previous sub-section, and the models are:
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\begin{enumerate}
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\item \textit{\gls{rtholt}},
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\textit{\gls{rtses}}, and
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\textit{\gls{rttheta}}:
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Exponential smoothing without calibration and seasonal fit
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\item \textit{\gls{rtets}}:
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ETS calibrated as described by \cite{hyndman2008b}
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\item \textit{\gls{rtarima}}:
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ARIMA calibrated as described by \cite{hyndman2008a}
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\end{enumerate}
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Retraining \textit{fnaive} and \textit{pnaive} did not increase accuracy, and
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thus we left them out.
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A downside of this family is the significant increase in computing costs.
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