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Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Bayesian Spatial Durbin Model× | Географічно зважена регресія (GWR)× | |
|---|---|---|
| Галузь | Просторовий аналіз | Просторовий аналіз |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2009 | 2002 |
| Автор методу≠ | LeSage & Pace | Fotheringham, Brunsdon & Charlton |
| Тип≠ | Bayesian spatial regression | Local spatial regression |
| Основоположне джерело≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168 |
| Інші назви | Bayesian SDM, Bayesian spatial lag-X model, Bayesian SDM with spatially lagged covariates, BSDM | GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR) |
| Пов'язані≠ | 6 | 5 |
| Підсумок≠ | The Bayesian Spatial Durbin Model (BSDM) estimates a spatial regression that simultaneously includes a spatially lagged outcome variable and spatially lagged covariates, using Bayesian inference with Markov Chain Monte Carlo sampling. It captures both endogenous and exogenous spatial spillovers while providing full posterior distributions for all parameters, quantifying uncertainty beyond what classical maximum-likelihood estimation offers. | Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships. |
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