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| Bayesova prostorna regresija× | Model prostornog zaostajanja (SAR / Prostorni autoregresijski)× | |
|---|---|---|
| Područje | Prostorna analiza | Prostorna analiza |
| Obitelj | Regression model | Regression model |
| Godina nastanka≠ | 1990s–2000s | 1988 |
| Tvorac≠ | Banerjee, Carlin & Gelfand (foundational treatment); building on Besag (1974) for lattice priors | Anselin (textbook formalisation); LeSage & Pace |
| Vrsta≠ | Bayesian hierarchical regression | Spatial autoregressive regression |
| Temeljni izvor≠ | 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 ↗ |
| Drugi nazivi | 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) |
| Srodne≠ | 3 | 5 |
| Sažetak≠ | 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. |
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