השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| TAR / SETAR: אוטורגרסיה סף עבור סדרות עתיות עם מעברי משטר× | מודל STAR (Smooth Transition Autoregressive)× | |
|---|---|---|
| תחום | אקונומטריקה | אקונומטריקה |
| משפחה | Regression model | Regression model |
| שנת המקור≠ | 1990 | 1994 |
| הוגה השיטה≠ | Howell Tong | Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002) |
| סוג≠ | Nonlinear time-series model with regime switching | Nonlinear time-series regime-switching model |
| מקור מכונן≠ | Tong, H. (1990). Non-linear Time Series: A Dynamical System Approach. Oxford University Press. ISBN: 978-0-19-852300-6 | Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗ |
| כינויים≠ | Threshold Autoregression, Self-Exciting Threshold Autoregression, SETAR Model, Eşik Otoregresyon | smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR |
| קשורות≠ | 2 | 4 |
| תקציר≠ | TAR and SETAR are nonlinear autoregressive models introduced by Howell Tong (1990) that allow a time series to follow different linear dynamics in distinct regimes, separated by one or more threshold values. SETAR is the self-exciting variant, in which the threshold variable is a lagged value of the series itself, making it particularly suited to cycles, asymmetric adjustment, and limit-cycle behavior observed in economic and financial data. | The Smooth Transition Autoregressive (STAR) model is a nonlinear time-series model, developed in Teräsvirta's 1994 framework, that lets the dynamics move smoothly rather than abruptly between two regimes. The logistic variant (LSTAR) captures asymmetric business cycles and the exponential variant (ESTAR) captures purchasing-power-parity deviations. |
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