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공간 SAC 모형×공간 시차 모형 (SAR / 공간 자기회귀)×
분야공간분석공간분석
계열Regression modelRegression model
기원 연도20091988
창시자James LeSage & R. Kelley PaceAnselin (textbook formalisation); LeSage & Pace
유형Combined spatial dependence regression modelSpatial autoregressive regression
원전LeSage, J., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press. ISBN: 978-1-4200-6424-7Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗
별칭SARAR Model, Spatial Autoregressive Model with Autoregressive Disturbances, Cliff-Ord Combined Model, Uzamsal Otoregresif Birleşik ModelSAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
관련35
요약The Spatial Autoregressive Combined (SAC) model, also known as the SARAR model, simultaneously accounts for spatial dependence in both the dependent variable and the error term. Formalized by LeSage and Pace (2009), the SAC model combines the spatial lag model and the spatial error model into a single framework, estimating two distinct spatial autoregressive parameters — one capturing substantive spatial interaction among outcomes and another capturing residual spatial correlation among disturbances.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.
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