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Nonlinear AR Model/Evidence
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.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Nonlinear Autoregressive Model
Taxonomic method record · 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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Curated claims

Claims persisted in the evidence ledger, each with its own assessment.

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketARIMA modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketARMA modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketAutoregressive modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketNonlinear ARDLmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketNonlinear VECMmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketStructural Break AR Modelmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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