Сравнение методов

	Байесовская модель пространственных ошибок	Пространственная модель ошибок (Spatial Error Model, SEM)
Область	Пространственный анализ	Пространственный анализ
Семейство	Regression model	Regression model
Год появления	1988 (classical SEM); 2009 (Bayesian formulation)	1988
Автор метода	LeSage & Pace (Bayesian treatment); Anselin (classical SEM)	Anselin
Тип	Bayesian spatial regression	Spatial regression (spatially autocorrelated errors)
Основополагающий источник	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.
Другие названия	Bayesian SEM, Bayesian spatial-error regression, BSEM spatial econometrics, Bayesian spatially correlated error model	SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error)
Связанные	6	5
Сводка	The Bayesian Spatial Error Model (Bayesian SEM) estimates a regression in which spatially correlated disturbances are explicitly modelled through a spatial weights matrix, while all parameters — regression coefficients, spatial error autocorrelation, and error variance — receive full posterior distributions via Bayesian inference rather than point estimates.	The Spatial Error Model, developed within Anselin's spatial econometrics framework (1988), is a regression model that assumes spatial dependence enters through the error term: the disturbances of neighbouring units are correlated. It is used when unobserved shared factors make the errors of nearby observations move together, and it is estimated by maximum likelihood or GMM rather than ordinary least squares.