Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Пространственно-временная пространственная регрессия× | Пространственная модель ошибок (Spatial Error Model, SEM)× | |
|---|---|---|
| Область | Пространственный анализ | Пространственный анализ |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1990s–2000s | 1988 |
| Автор метода≠ | Anselin, LeSage, Pace and colleagues in spatial econometrics | Anselin |
| Тип≠ | Spatio-temporal regression model | Spatial regression (spatially autocorrelated errors) |
| Основополагающий источник≠ | 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. DOI ↗ |
| Другие названия | spatio-temporal regression, spatial panel regression, space-time regression, ST spatial regression | SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error) |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Space-Time Spatial Regression extends classical spatial regression to panel settings where georeferenced units are observed across multiple time periods. By embedding a spatial weights matrix into a panel regression framework, it simultaneously controls for spatial dependence among cross-sectional units and temporal dynamics, yielding unbiased and consistent estimates in spatio-temporal data. | 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 данных ↗ |
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