Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Пространствен лаг модел (SAR / Spatial Autoregressive)× | Пространствен модел на грешката (SEM)× | |
|---|---|---|
| Област | Пространствен анализ | Пространствен анализ |
| Семейство | Regression model | Regression model |
| Година на възникване | 1988 | 1988 |
| Създател≠ | Anselin (textbook formalisation); LeSage & Pace | Anselin |
| Тип≠ | Spatial autoregressive regression | Spatial regression (spatially autocorrelated errors) |
| Основополагащ източник | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ |
| Други названия | SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag) | SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error) |
| Свързани | 5 | 5 |
| Резюме≠ | The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts. | The Spatial Error Model, developed within Anselin's spatial econometrics framework (1988), is a regression model that assumes spatial dependence enters through the error term: the disturbances of neighbouring units are correlated. It is used when unobserved shared factors make the errors of nearby observations move together, and it is estimated by maximum likelihood or GMM rather than ordinary least squares. |
| ScholarGateНабор от данни ↗ |
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