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Bayesiansk spatial Durbin-modell×Spatial Lag Model (SAR / Spatial Autoregressive)×
ÄmnesområdeRumslig analysRumslig analys
FamiljRegression modelRegression model
Ursprungsår20091988
UpphovspersonLeSage & PaceAnselin (textbook formalisation); LeSage & Pace
TypBayesian spatial regressionSpatial autoregressive regression
UrsprungskällaLeSage, 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 ↗
AliasBayesian 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)
Närliggande65
SammanfattningThe 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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ScholarGateJämför metoder: Bayesian Spatial Durbin Model · Spatial Lag Model. Hämtad 2026-06-17 från https://scholargate.app/sv/compare