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Bayesovský priestorový Durbinov model×Geograficky vážená regresia (GWR)×
OdborPriestorová analýzaPriestorová analýza
RodinaRegression modelRegression model
Rok vzniku20092002
TvorcaLeSage & PaceFotheringham, Brunsdon & Charlton
TypBayesian spatial regressionLocal spatial regression
Pôvodný zdrojLeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Ďalšie názvyBayesian SDM, Bayesian spatial lag-X model, Bayesian SDM with spatially lagged covariates, BSDMGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Príbuzné65
ZhrnutieThe 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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ScholarGatePorovnať metódy: Bayesian Spatial Durbin Model · Geographically Weighted Regression. Získané 2026-06-18 z https://scholargate.app/sk/compare