Сравнение на методи
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| Нелинеен авторегресивен (NAR) модел× | Модел на авторегресия със структурни промени× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1978-1990 | 1989-2003 |
| Създател≠ | 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 |
| Основополагащ източник≠ | 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. DOI ↗ |
| Други 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 |
| Свързани | 6 | 6 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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