Damped Trend Exponential Smoothing: Prediction and Control
نویسنده
چکیده
Damped trend exponential smoothing models have gained importance in empirical studies due to their remarkable forecasting performance. This paper derives their theoretical forecast error variance, based on the implied ARIMA model, as algebraic function of the structural parameters. As a consequence, the minimum mean squared error (MMSE) forecasts as well as the h-step ahead theoretical forecast error variances can also be expressed as algebraic (and unique) functions of the structural parameters. Analytical results are provided for the random coefficient state space model, as introduced by McKenzie and Gardner (2010) “Damped trend exponential smoothing: A modeling viewpoint”, International Journal of Forecasting, 26 (4), 661-665, in the single source of error context. Moreover, algebraic results are also given for standard Holt-Winters (damped) trend models in the multiple sources of errors context.
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