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مدل ترکیبی خودهمبستگی فضایی (SAC)×مدل وقفه فضایی (SAR / خودرگرسیون فضایی)×
حوزهتحلیل فضاییتحلیل فضایی
خانوادهRegression modelRegression model
سال پیدایش20091988
پدیدآورJames LeSage & R. Kelley PaceAnselin (textbook formalisation); LeSage & Pace
نوعCombined spatial dependence regression modelSpatial autoregressive regression
منبع بنیادینLeSage, 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 ↗
نام‌های دیگرSARAR 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)
مرتبط35
خلاصهThe 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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ScholarGateمقایسهٔ روش‌ها: Spatial SAC Model · Spatial Lag Model. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare