方法证据记录
Nonlinear AR Model
The Nonlinear AR model extends the classical autoregressive framework by allowing the mapping from past values to the current value to follow an arbitrary or regime-switching nonlinear function. Major families include the Self-Exciting Threshold AR (SETAR), Smooth Transition AR (STAR), and neural network AR, each capturing different forms of asymmetry, regime shifts, or smooth nonlinear dynamics in univariate time series.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Nonlinear Autoregressive Model
分类方法记录 · regression-model / econometrics
- Tong, H. (1990). Non-Linear Time Series: A Dynamical System Approach. Oxford University Press. · ISBN 9780198522201
- Terasvirta, T. (1994). Specification, estimation, and evaluation of smooth transition autoregressive models. Journal of the American Statistical Association, 89(425), 208-218. · DOI 10.1080/01621459.1994.10476462
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