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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.

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Nonlinear Autoregressive Model

Taksonomisk metoderegister · 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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