Сравнение методов

	Нелинейная авторегрессионная (NAR) модель	Модель АР с структурными сдвигами
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1978-1990	1989-2003
Автор метода	Tong, H. (threshold AR); Terasvirta, T. (STAR variant)	Perron (1989); Bai & Perron (1998, 2003)
Тип	Nonlinear time series model	Time-series model with structural change
Основополагающий источник	Tong, H. (1990). Non-Linear Time Series: A Dynamical System Approach. Oxford University Press. ISBN: 9780198522201	Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 1-22.
Другие названия	NAR model, nonlinear autoregression, NLAR, threshold autoregressive model	AR model with structural change, breakpoint AR model, piecewise autoregressive model, AR model with regime shifts
Связанные	6	6
Сводка	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.	The structural break AR model extends the standard autoregressive framework by allowing the intercept and autoregressive coefficients to shift at one or more unknown break dates. Each regime between consecutive break points is governed by its own AR parameters, capturing abrupt changes in the dynamics of a time series caused by crises, policy shifts, or other shocks.