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- W418969867 abstract "In Chapter 11, we described how Bayesian inference can be applied to hierarchical models. In this chapter, we show how the members of a model class, indexed by m, can also be considered as part of a hierarchy. Model classes might be general linear models (GLMs) where m indexes different choices for the design matrix, dynamic causal models (DCMs) where m indexes connectivity or input patterns, or source reconstruction models where m indexes functional or anatomical constraints. Explicitly including model structure in this way will allow us to make inferences about that structure." @default.
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- W418969867 date "2007-01-01" @default.
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- W418969867 title "Bayesian model selection and averaging" @default.
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- W418969867 doi "https://doi.org/10.1016/b978-012372560-8/50035-8" @default.
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