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A Bayesian Approach to Short-term Forecasting
Abstract
A new approach to short-term forecasting is described, based on Bayesian principles. The performance of conventional systems is often upset by the occurrence of changes in trend and slope, or transients. In this approach events of this nature are modelled explicitly, and successive data points are used to calculate the posterior probabilities of such events at each instant of time.The system produces not only single-figure forecasts but distributions of trend and slope values which are relevant to subsequent decisions based on forecasts.
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Citations
Cited by
Harrison, P. J., & Stevens, C. F. (1976) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1976.tb01586.x · Cited by 649
Self-citationData fusion in intelligent transportation systems: Progress and challenges – A survey
Faouzi, N.-E. E., Leung, H., & Kurian, A. (2011) · Information Fusion · doi:10.1016/j.inffus.2010.06.001 · Cited by 444
Forecasting and operational research: a review
Fildes, R., Nikolopoulos, K., Crone, S. F., & Syntetos, A. A. (2008) · Journal of the Operational Research Society · doi:10.1057/palgrave.jors.2602597 · Cited by 287
Metadata
- Authors
- Harrison, P. J., & Stevens, C. F.
- Venue
- Journal of the Operational Research Society
- Publisher
- Informa UK Limited
- Published
- 1971-12
- Volume
- 22
- Issue
- 4
- Pages
- 341-362
- ISSN
- 0160-5682 (ISSN-L)
- 1476-9360
- OpenAlex
- W2090650813
- Cited by
- 210
- References
- 0
- FWCI
- 5.16
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A Bayesian Approach to Short-term Forecasting. https://app.cochat.ai/papers/10.1057/jors.1971.78
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- Harrison, P. J., & Stevens, C. F. (1971). A Bayesian Approach to Short-term Forecasting. Journal of the Operational Research Society. https://doi.org/10.1057/jors.1971.78
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
