10.4225/03/593797110eca0
Snyder, Ralph D.
Ralph D.
Snyder
Exponential smoothing: a prediction error decomposition principle
Monash University
2017
Exponential smoothing
State space models
Time series analysis
monash:2354
Prediction
2004
ARIMA models
1959.1/2354
2017-06-07 06:02:55
Journal contribution
https://bridges.monash.edu/articles/journal_contribution/Exponential_smoothing_a_prediction_error_decomposition_principle/5085475
In the exponential smoothing approach to forecasting, restrictions are often imposed on the smoothing parameters which ensure that certain components are exponentially weighted averages. In this paper, a new general restriction is derived on the basis that the one-step ahead prediction error can be decomposed into permanent and transient components. It is found that this general restriction reduces to the common restrictions used for simple, trend and seasonal exponential smoothing. As such, the prediction error argument provides the rationale for these restrictions.