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Priestorové bayesovské priemerovanie modelov×Bayesovské spriemerovanie modelov×
OdborBayesovské metódyBayesovské metódy
RodinaBayesian methodsBayesian methods
Rok vzniku20081999
TvorcaLeSage & Fischer (building on Raftery et al. BMA framework, 1997)Hoeting, Madigan, Raftery & Volinsky
TypBayesian model combination with spatial structureBayesian model averaging
Pôvodný zdrojLeSage, J. P. & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247Hoeting, J. A., Madigan, D., Raftery, A. E. & Volinsky, C. T. (1999). Bayesian Model Averaging: A Tutorial. Statistical Science, 14(4), 382–401. link ↗
Ďalšie názvyspatial BMA, BMA for spatial data, Bayesian model averaging with spatial effects, spatial model uncertainty averagingBMA, Bayesian model combination, Bayesian Model Ortalaması (BMA)
Príbuzné55
ZhrnutieSpatial 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 Model Averaging (BMA), formalised as a tutorial by Hoeting, Madigan, Raftery and Volinsky in 1999, addresses model uncertainty by averaging over all plausible model specifications rather than selecting a single best model. Each candidate model receives a posterior probability that reflects how well it fits the data given a prior, and predictions or coefficient estimates are formed as weighted averages across the entire model space. This approach reduces the bias and overconfidence that arise when a single selected model is treated as the true one.
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ScholarGatePorovnať metódy: Spatial Bayesian Model Averaging · Bayesian Model Averaging. Získané 2026-06-15 z https://scholargate.app/sk/compare