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Modelo Espacial Durbin Bayesiano×Modelo de Lag Espacial (SAR / Autoregressivo Espacial)×
ÁreaAnálise espacialAnálise espacial
FamíliaRegression modelRegression model
Ano de origem20091988
Autor originalLeSage & PaceAnselin (textbook formalisation); LeSage & Pace
TipoBayesian spatial regressionSpatial autoregressive regression
Fonte seminalLeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗
Outros nomesBayesian SDM, Bayesian spatial lag-X model, Bayesian SDM with spatially lagged covariates, BSDMSAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
Relacionados65
ResumoThe 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 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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ScholarGateComparar métodos: Bayesian Spatial Durbin Model · Spatial Lag Model. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare