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	Spatial Bayesian Model Averaging	Bayesiansk regression
Ämnesområde	Bayesiansk statistik	Bayesiansk statistik
Familj	Bayesian methods	Bayesian methods
Ursprungsår	2008	—
Upphovsperson	LeSage & Fischer (building on Raftery et al. BMA framework, 1997)	—
Typ	Bayesian model combination with spatial structure	Bayesian linear model
Ursprungskälla	LeSage, J. P. & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247	Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955
Alias	spatial BMA, BMA for spatial data, Bayesian model averaging with spatial effects, spatial model uncertainty averaging	bayesian linear regression, probabilistic regression, bayesian regresyon
Närliggande	5	2
Sammanfattning	Spatial Bayesian model averaging (spatial BMA) extends classical BMA to settings where observations are georeferenced and spatial dependence must be modelled. Rather than selecting a single spatial regression model — which spatial weight matrix to use, which regressors to include, which spatial lag or error structure to adopt — it averages the predictions and parameter estimates across all candidate models, weighting each by its posterior probability given the data.	Bayesian regression is a probabilistic version of linear regression that treats the model parameters as uncertain quantities. Instead of returning a single best-fit estimate, it combines prior knowledge with the observed data to produce a full posterior probability distribution for each parameter, from which credible intervals and predictions are read off.