Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Глобальная пространственная модель Дурбина (SDM)× | Пространственная модель ошибок (Spatial Error Model, SEM)× | |
|---|---|---|
| Область | Пространственный анализ | Пространственный анализ |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2009 | 1988 |
| Автор метода≠ | Durbin (1960); adapted to spatial context by LeSage & Pace (2009) | Anselin |
| Тип≠ | Spatial 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 | SDM, Spatial Durbin Model, global SDM, spatially lagged X model with spatial lag | SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error) |
| Связанные | 5 | 5 |
| Сводка≠ | 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 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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