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| نموذج الانحدار الذاتي المكاني البيزي (BSLM)× | الارتباط التلقائي المكاني× | |
|---|---|---|
| المجال | التحليل المكاني | التحليل المكاني |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 1997 | 1950 |
| صاحب الطريقة≠ | LeSage (1997); fully elaborated in LeSage & Pace (2009) | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| النوع≠ | Bayesian spatial regression | Spatial statistic / exploratory spatial data analysis |
| المصدر التأسيسي≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| الأسماء البديلة | Bayesian SAR model, Bayesian spatial autoregressive model, BSLM, Bayesian SLM | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| ذات صلة | 5 | 5 |
| الملخص≠ | The Bayesian Spatial Lag Model (BSLM) extends the classical spatial autoregressive (SAR) regression by placing prior distributions over all parameters and recovering full posterior distributions via MCMC sampling. It explicitly accounts for spatial dependence — the outcome in one location is partly driven by outcomes in neighboring locations — and yields uncertainty-quantified estimates of both regression coefficients and the spatial autocorrelation parameter rho. | Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations. |
| ScholarGateمجموعة البيانات ↗ |
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