The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models
Abstract
This article considers the application of two families of nonlinear autoregressive models, the logistic (LSTAR) and exponential (ESTAR) autoregressive models. This includes the specification of the model based on simple statistical tests: linearity testing against smooth transition autoregression, determining the delay parameter and choosing between LSTAR and ESTAR models are discussed. Estimation by nonlinear least squares is considered as well as evaluating the properties of the estimated model. The proposed techniques are illustrated by examples using both simulated and real time series.
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Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
Cited by
Forecast Methods for Time Series Data: A Survey
Liu, Z., Zhu, Z., Gao, J., & Xu, C. (2021) · IEEE Access · doi:10.1109/access.2021.3091162 · Cited by 247
Population aging and fiscal sustainability: Nonlinear evidence from Europe
Cho, D., & Lee, K.-W. (2022) · Journal of International Money and Finance · doi:10.1016/j.jimonfin.2022.102665 · Cited by 40
Metadata
- Authors
- Teräsvirta, T.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1994-03
- Volume
- 89
- Issue
- 425
- Pages
- 208-218
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2118234389
- Cited by
- 2,242
- References
- 2
- FWCI
- 17.99
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
