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Method evidence record

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.

Evidence statusSources recorded, not reviewedBibliographic sources are present. Claim-level evidence review has not been performed.

Source record

Recorded

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Nonlinear Autoregressive Model

Taxonomic method recordregression-modeleconometrics

  1. Tong, H. (1990). Non-Linear Time Series: A Dynamical System Approach. Oxford University Press. · ISBN 9780198522201

  2. 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

Open full method2 recorded citations, copied from the method source record.

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Related methods

Suggested6

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