विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| ग्लोबल स्पैशियल डर्बिन मॉडल (SDM)× | ग्लोबल स्पैशियल एरर मॉडल (SEM)× | |
|---|---|---|
| क्षेत्र | स्थानिक विश्लेषण | स्थानिक विश्लेषण |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 2009 | 1988 |
| प्रवर्तक≠ | Durbin (1960); adapted to spatial context by LeSage & Pace (2009) | Luc Anselin |
| प्रकार | Spatial regression model | Spatial regression model |
| मौलिक स्रोत≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. ISBN: 978-9024737322 |
| उपनाम | SDM, Spatial Durbin Model, global SDM, spatially lagged X model with spatial lag | SEM, spatial error model, spatial error regression, global SEM |
| संबंधित | 5 | 5 |
| सारांश≠ | The Global Spatial Durbin Model extends the spatial lag model by including not only a spatially lagged dependent variable but also spatially lagged independent variables (WX). A single set of global coefficients applies uniformly across all locations, making it suitable for estimating average spillover effects when spatial dependence is pervasive throughout the study region. | The Global Spatial Error Model (SEM) is a spatial regression technique that accounts for spatially autocorrelated error terms using a single, globally constant spatial parameter. It separates genuine predictor effects from spatial nuisance dependence in the residuals, yielding unbiased and efficient coefficient estimates when spatial error correlation is present across all observations. |
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