Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Telpiskā regresija (telpiskā nobīdes un telpiskās kļūdas modeļi)× | Regresija ar slieksni× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1988 | 2000 |
| Autors≠ | Luc Anselin | Bruce E. Hansen |
| Tips≠ | Spatial regression (cross-sectional) | Nonlinear regime-switching regression |
| Pirmavots≠ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. DOI ↗ | Hansen, B. E. (2000). Sample Splitting and Threshold Estimation. Econometrica, 68(3), 575-603. DOI ↗ |
| Citi nosaukumi≠ | spatial econometrics, spatial lag model, spatial error model, SAR / SEM | threshold model, regime-switching regression, sample splitting model, Eşik Değer Regresyonu (Threshold Regression) |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | Spatial regression is a family of regression models that build geographic neighbourhood relationships directly into the model, introduced by Luc Anselin in his 1988 treatment of spatial econometrics. It splits into a spatial lag model, where spatial dependence sits in the dependent variable, and a spatial error model, where the dependence sits in the error term. | Threshold regression is a nonlinear, regime-switching model in which the regression parameters take different values above and below an estimated threshold value of a threshold variable. The sample-splitting and threshold-estimation framework was developed by Bruce E. Hansen (2000) and is widely used for time-series and panel data with structural breaks and regime-dependent relationships. |
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