Σύγκριση μεθόδων
Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Παγκόσμιο Χωρικό Μοντέλο Durbin (SDM)× | Μοντέλο Παγκόσμιου Χωρικού Σφάλματος (SEM)× | |
|---|---|---|
| Πεδίο | Χωρική Ανάλυση | Χωρική Ανάλυση |
| Οικογένεια | Regression model | Regression model |
| Έτος προέλευσης≠ | 2009 | 1988 |
| Δημιουργός≠ | Durbin (1960); adapted to spatial context by LeSage & Pace (2009) | Luc Anselin |
| Τύπος | Spatial regression model | Spatial regression model |
| Θεμελιώδης πηγή≠ | 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 |
| Εναλλακτικές ονομασίες | SDM, Spatial Durbin Model, global SDM, spatially lagged X model with spatial lag | SEM, spatial error model, spatial error regression, global SEM |
| Συναφείς | 5 | 5 |
| Σύνοψη≠ | 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. |
| ScholarGateΣύνολο δεδομένων ↗ |
|
|