Working Papers 2004 – Abstracts
15/2004
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Exponential Smoothing: A Prediction Error Decomposition Principle
Ralph D. Snyder
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.
Keywords: time series analysis, prediction, exponential smoothing,
ARIMA models, state space models.
