Сравнение на методи

	Байесов модел на пространствено изоставане	Пространствен лаг модел (SAR / Spatial Autoregressive)
Област	Пространствен анализ	Пространствен анализ
Семейство	Regression model	Regression model
Година на възникване	1997	1988
Създател	LeSage (1997); fully elaborated in LeSage & Pace (2009)	Anselin (textbook formalisation); LeSage & Pace
Тип	Bayesian spatial regression	Spatial autoregressive regression
Основополагащ източник	LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247	Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic.
Други названия	Bayesian SAR model, Bayesian spatial autoregressive model, BSLM, Bayesian SLM	SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag)
Свързани	5	5
Резюме	The Bayesian Spatial Lag Model (BSLM) extends the classical spatial autoregressive (SAR) regression by placing prior distributions over all parameters and recovering full posterior distributions via MCMC sampling. It explicitly accounts for spatial dependence — the outcome in one location is partly driven by outcomes in neighboring locations — and yields uncertainty-quantified estimates of both regression coefficients and the spatial autocorrelation parameter rho.	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.