विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| पैनल मल्टीस्केल ज्योग्राफिकली वेटेड रिग्रेशन (पैनल MGWR)× | पैनल स्पैटियल डर्बिन मॉडल× | |
|---|---|---|
| क्षेत्र | स्थानिक विश्लेषण | स्थानिक विश्लेषण |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 2017-2020 | 2009–2010 |
| प्रवर्तक≠ | Fotheringham, Yang & Kang (MGWR base); panel extension developed in spatial econometrics literature | LeSage & Pace (2009); panel extension by Elhorst (2010) |
| प्रकार≠ | Spatially varying coefficient panel regression | Spatial panel regression |
| मौलिक स्रोत≠ | 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 |
| उपनाम | Panel MGWR, MGWR panel data, multiscale GWR panel, panel spatially varying coefficient model | SDM panel, spatial Durbin panel model, panel SDM, PSDM |
| संबंधित | 5 | 5 |
| सारांश≠ | 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 Durbin Model (PSDM) extends the cross-sectional Spatial Durbin Model to panel data, capturing both spatial lag dependence in the outcome and spatial spillovers from neighbouring units' explanatory variables across multiple time periods. It simultaneously accounts for unobserved unit-specific and time-specific heterogeneity, making it one of the most comprehensive spatial panel specifications available. |
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