Economics at your fingertips  

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
References: Add references at CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed

Published in: Journal of Forecasting (1990) v.9 n° 5,p.445-455

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This working paper can be ordered from ...

Access Statistics for this paper

More papers in ULB Institutional Repository from ULB -- Universite Libre de Bruxelles Contact information at EDIRC.
Bibliographic data for series maintained by Benoit Pauwels ().

Page updated 2020-08-02
Handle: RePEc:ulb:ulbeco:2013/13716