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Exponential smoothing: estimation by maximum likelihood

Laurence Broze () and Guy Melard

ULB Institutional Repository from ULB -- Universite Libre de Bruxelles

Abstract: In this paper several forecasting methods based on exponential smoothing with an underlying seasonal autoregressive‐moving average (SARIMA) model are considered. The relations between the smoothing constants and the coefficients of the autoregressive and moving average polynomials are used. On that basis, a maximum likelihood procedure for parameter estimation is described. The approach rules out the need for initial smoothed values. Prediction intervals are also obtained as a by‐product of the approach and a fast algorithm for implementing the method is outlined. Copyright © 1990 John Wiley & Sons, Ltd.

Keywords: Box‐Jenkins methodology; Exponential smoothing; Maximum likelihood estimation; Time series ARIMA models (search for similar items in EconPapers)
Date: 1990
Note: SCOPUS: ar.j
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Published in: Journal of Forecasting (1990) v.9 n° 5,p.445-455

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