विधियों की तुलना करें

	बायेसियन स्थानिक डर्बिन मॉडल	स्थानिक डर्बिन मॉडल (SDM)
क्षेत्र	स्थानिक विश्लेषण	स्थानिक विश्लेषण
परिवार	Regression model	Regression model
उद्भव वर्ष	2009	2009
प्रवर्तक	LeSage & Pace	LeSage & Pace
प्रकार	Bayesian spatial regression	Spatial regression model
मौलिक स्रोत	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247	LeSage, J. & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press.
उपनाम	Bayesian SDM, Bayesian spatial lag-X model, Bayesian SDM with spatially lagged covariates, BSDM	SDM, spatial mixed model, uzamsal durbin modeli
संबंधित	6	5
सारांश	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 Spatial Durbin Model is a general spatial regression model that includes a spatial lag of both the dependent variable (ρWy) and the explanatory variables (WXθ). Introduced as the recommended starting point by LeSage and Pace (2009), it nests the spatial autoregressive (SAR) and spatial error (SEM) models as special cases.