Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Panel Multiscale Geographically Weighted Regression× | Modeli wa Hitilafu za Kina za Paneli (Panel Spatial Error Model)× | |
|---|---|---|
| Nyanja | Uchanganuzi wa Kimaeneo | Uchanganuzi wa Kimaeneo |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 2017-2020 | 1988 / 2003 |
| Mwanzilishi≠ | Fotheringham, Yang & Kang (MGWR base); panel extension developed in spatial econometrics literature | Anselin (1988); extended to panels by Elhorst (2003, 2014) |
| Aina≠ | Spatially varying coefficient panel regression | Spatial econometric panel model |
| Chanzo asilia≠ | Fotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale Geographically Weighted Regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265. DOI ↗ | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408 |
| Majina mbadala | Panel MGWR, MGWR panel data, multiscale GWR panel, panel spatially varying coefficient model | panel SEM, spatial error panel model, panel spatial autocorrelation error model, SEM panel |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | Panel MGWR extends Multiscale Geographically Weighted Regression to repeated-observations (panel) data, allowing each predictor to operate at its own spatial bandwidth while controlling for unit-specific or time-specific fixed effects. It is used when both spatial heterogeneity and temporal structure matter simultaneously. | The Panel Spatial Error Model (panel SEM) extends the classical spatial error model to panel data, allowing spatial dependence to enter through the error term across cross-sectional units over multiple time periods. It accounts for spatially correlated omitted variables without imposing a substantive spatial spillover in the outcome itself. |
| ScholarGateSeti ya data ↗ |
|
|