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| الانحدار المكاني البيزي× | نموذج التباطؤ المكاني (SAR / الانحدار الذاتي المكاني)× | |
|---|---|---|
| المجال | التحليل المكاني | التحليل المكاني |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 1990s–2000s | 1988 |
| صاحب الطريقة≠ | Banerjee, Carlin & Gelfand (foundational treatment); building on Besag (1974) for lattice priors | Anselin (textbook formalisation); LeSage & Pace |
| النوع≠ | Bayesian hierarchical regression | Spatial autoregressive regression |
| المصدر التأسيسي≠ | Banerjee, S., Carlin, B. P., & Gelfand, A. E. (2015). Hierarchical Modeling and Analysis for Spatial Data (2nd ed.). CRC Press. ISBN: 978-1439819173 | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ |
| الأسماء البديلة | Bayesian hierarchical spatial model, BSR, Bayesian geostatistical regression, Bayesian spatial linear model | SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag) |
| ذات صلة≠ | 3 | 5 |
| الملخص≠ | Bayesian Spatial Regression embeds a spatially structured random effect into a regression framework and estimates all parameters — including spatial range and variance — through posterior inference rather than point estimation. It handles spatial autocorrelation, quantifies full predictive uncertainty, and accommodates small or irregular spatial datasets via hierarchical priors. | 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. |
| ScholarGateمجموعة البيانات ↗ |
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