The DOI matches its Crossref record.
The theta model: a decomposition approach to forecasting
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Citations
Cited by
Another look at measures of forecast accuracy
Hyndman, R. J., & Koehler, A. B. (2006) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2006.03.001 · Cited by 5,757
Electricity price forecasting: A review of the state-of-the-art with a look into the future
Weron, R. (2014) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2014.08.008 · Cited by 1,646
Statistical and machine learning forecasting methods: Concerns and ways forward
Makridakis, S., Spiliotis, E., & Assimakopoulos, V. (2018) · PLOS ONE · doi:10.1371/journal.pone.0194889 · Cited by 1,528
Self-citationKalfarisi, R., Chew, A., Cai, J., Xue, M., Pok, J., & Wu, Z. Y. (2022) · Advances in Engineering Software · doi:10.1016/j.advengsoft.2022.103287 · Cited by 10
Saini, S., Manai, G., van den Boom, W., De Iorio, M., & Qian, F. (2024) · Discover Analytics · doi:10.1007/s44257-024-00013-2 · Cited by 1
Metadata
- Authors
- Assimakopoulos, V., & Nikolopoulos, K.
- Venue
- International Journal of Forecasting
- Publisher
- Elsevier BV
- Published
- 2000-10
- Volume
- 16
- Issue
- 4
- Pages
- 521-530
- ISSN
- 0169-2070 (ISSN-L)
- OpenAlex
- W1977698057
- Cited by
- 503
- References
- 0
- FWCI
- 4.68
- Type
- journal article
- Language
- en
- Open access
- green
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The theta model: a decomposition approach to forecasting. https://app.cochat.ai/papers/10.1016/s0169-2070(00)00066-2
- The paper
- Assimakopoulos, V., & Nikolopoulos, K. (2000). The theta model: a decomposition approach to forecasting. International Journal of Forecasting. https://doi.org/10.1016/s0169-2070(00)00066-2
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.
