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Пространствена регресия (модели с пространствен лаг и пространствена грешка)×Привидно несвързани регресии (SUR)×
ОбластИконометрияИконометрия
СемействоRegression modelRegression model
Година на възникване19881962
СъздателLuc AnselinArnold Zellner
ТипSpatial regression (cross-sectional)System regression (multi-equation)
Основополагащ източникAnselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. DOI ↗Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association, 57(298), 348-368. DOI ↗
Други названияspatial econometrics, spatial lag model, spatial error model, SAR / SEMSUR, Zellner's SUR, seemingly unrelated regression equations, Görünürde İlişkisiz Regresyon (SUR)
Свързани55
РезюмеSpatial regression is a family of regression models that build geographic neighbourhood relationships directly into the model, introduced by Luc Anselin in his 1988 treatment of spatial econometrics. It splits into a spatial lag model, where spatial dependence sits in the dependent variable, and a spatial error model, where the dependence sits in the error term.Seemingly Unrelated Regressions, introduced by Arnold Zellner in 1962, is a system regression method that estimates several linear equations jointly when their error terms are correlated across equations. By exploiting that cross-equation correlation through generalized least squares, it is more efficient than estimating each equation separately by OLS.
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  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 1 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Spatial Regression · Seemingly Unrelated Regression. Извлечено на 2026-06-18 от https://scholargate.app/bg/compare