Article
Thermodynamic integration for dynamic causal models
2018-11-22
Abstract excerpt
In generative modeling of neuroimaging data, such as dynamic causal modeling (DCM), one typically considers several alternative models, either to determine the most plausible explanation for observed data (Bayesian model selection) or to account for model uncertainty (Bayesian model averaging). Both procedures rest on estimates of the model evidence, a principled trade-off between model accuracy and complexity. In...
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Identifiers and source
- Literature Corpus work
- 48cfff87-4fdb-5c2e-baf6-cbf31ea85ed1
- DOI
- 10.1101/471417