Journal article
Adaptive Filtering: An Empirical Evaluation
The Journal of the Operational Research Society, Vol.35(4), pp.337-345
04/01/1984
DOI: 10.1057/jors.1984.66
Abstract
This paper compares the Makridakis and Wheelwright adaptive filtering forecast technique with the recursive least squares procedure, which assumes constant coefficients. A simulation study is performed to examine its relative forecast accuracy under several models of time-varying coefficients. It is shown that the choice of the learning constant in adaptive filtering is quite critical, and that only in cases with substantial coefficient variability will adaptive filtering lead to forecast improvements.
Details
- Title: Subtitle
- Adaptive Filtering: An Empirical Evaluation
- Creators
- Johannes Ledolter - Southern Illinois University CarbondaleDouglas R. Kahl - Southern Illinois University Carbondale
- Resource Type
- Journal article
- Publication Details
- The Journal of the Operational Research Society, Vol.35(4), pp.337-345
- Publisher
- Taylor & Francis
- DOI
- 10.1057/jors.1984.66
- ISSN
- 0160-5682
- eISSN
- 1476-9360
- Language
- English
- Date published
- 04/01/1984
- Academic Unit
- Statistics and Actuarial Science; Business Analytics
- Record Identifier
- 9984380524802771
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