Note---Seasonal Exponential Smoothing with Damped Trends

Everette S. Gardner, Jr. and Ed. McKenzie
Additional contact information
Everette S. Gardner, Jr.: College of Business Administration, University of Houston, Houston, Texas 77004
Ed. McKenzie: Mathematics Department, University of Strathclyde, Glasgow, G1 1XW, Scotland, United Kingdom

Management Science, 1989, vol. 35, issue 3, 372-376

Abstract: In this paper we apply the strategy of trend-damping to the popular Winters exponential smoothing systems for seasonal time series. Efficient model formulations are derived for both multiplicative and additive seasonal patterns. An algorithm is given to test the stability of the models in cases where predetermined smoothing parameters are used. Empirical results are presented to show that trend-damping improves ex ante forecast accuracy in seasonal data, especially at long leadtimes.

Keywords: forecasting:; time; series (search for similar items in EconPapers)
Date: 1989
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.35.3.372 (application/pdf)

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: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:35:y:1989:i:3:p:372-376

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().