Journal article
A Recursive Kalman Filter Forecasting Approach
Management science, Vol.29(11), pp.1325-1333
11/01/1983
DOI: 10.1287/mnsc.29.11.1325
Abstract
This paper examines the forecasting accuracy and the cost effectiveness of time series models with time-varying coefficients. A simulation study investigates the potential forecasting benefits of a proposed Kalman filter type adaptive estimation and forecasting approach. It is found that: When appropriate, the time-varying coefficient approach leads to better forecasts than the constant coefficient procedures. A simple decision rule, which indicates whether time-varying coefficient models are in fact needed, increases the computational efficiency.
Details
- Title: Subtitle
- A Recursive Kalman Filter Forecasting Approach
- Creators
- Douglas R. Kahl - University of South DakotaJohannes Ledolter - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Management science, Vol.29(11), pp.1325-1333
- DOI
- 10.1287/mnsc.29.11.1325
- ISSN
- 0025-1909
- eISSN
- 1526-5501
- Language
- English
- Date published
- 11/01/1983
- Academic Unit
- Statistics and Actuarial Science; Business Analytics
- Record Identifier
- 9984380431202771
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