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| Bejzovski prostorni Durbinov model× | Bajezijanski model prostorne greške× | |
|---|---|---|
| Oblast | Prostorna analiza | Prostorna analiza |
| Porodica | Regression model | Regression model |
| Godina nastanka≠ | 2009 | 1988 (classical SEM); 2009 (Bayesian formulation) |
| Tvorac≠ | LeSage & Pace | LeSage & Pace (Bayesian treatment); Anselin (classical SEM) |
| Tip | Bayesian spatial regression | Bayesian spatial regression |
| Temeljni izvor | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 |
| Drugi nazivi | Bayesian SDM, Bayesian spatial lag-X model, Bayesian SDM with spatially lagged covariates, BSDM | Bayesian SEM, Bayesian spatial-error regression, BSEM spatial econometrics, Bayesian spatially correlated error model |
| Srodne | 6 | 6 |
| Sažetak≠ | 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. | The Bayesian Spatial Error Model (Bayesian SEM) estimates a regression in which spatially correlated disturbances are explicitly modelled through a spatial weights matrix, while all parameters — regression coefficients, spatial error autocorrelation, and error variance — receive full posterior distributions via Bayesian inference rather than point estimates. |
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