The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Threshold Autoregression, Limit Cycles and Cyclical Data
Abstract
Summary: The notion of a limit cycle, which can only exist in a non-linear system, plays the key role in the modelling of cyclical data. We have shown that the class of threshold autoregressive models is general enough to capture this notion, a definition of which in discrete time is proposed. The threshold value has an interesting interpretation. Simulation results are presented which demonstrate that this new class of models exhibits some well-known features of non-linear vibrations. Detailed analyses of several real data sets are discussed.
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Cites
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Cited by
Forecasting with artificial neural networks:
Zhang, G., Eddy Patuwo, B., & Y. Hu, M. (1998) · International Journal of Forecasting · doi:10.1016/s0169-2070(97)00044-7 · Cited by 4,229
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
DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED‐RESIDUAL AUTOCORRELATIONS
McLeod, A. I., & Li, W. K. (1983) · Journal of Time Series Analysis · doi:10.1111/j.1467-9892.1983.tb00373.x · Cited by 1,123
Chaos and Nonlinear Dynamics: Application to Financial Markets
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Testing and Modeling Threshold Autoregressive Processes
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Metadata
- Authors
- Tong, H., & Lim, K. S.
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 1980-07-01
- Volume
- 42
- Issue
- 3
- Pages
- 245-268
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W1606326889
- Cited by
- 1,309
- References
- 23
- FWCI
- 17.76
- Type
- journal article
- Language
- en
- Open access
- closed
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- Tong, H., & Lim, K. S. (1980). Threshold Autoregression, Limit Cycles and Cyclical Data. Journal of the Royal Statistical Society Series B: Statistical Methodology. https://doi.org/10.1111/j.2517-6161.1980.tb01126.x
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.
