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Summary
| Description |
English: Example priors. In a 'full' model, left, a parameter has a Gaussian prior with mean 0 and standard deviation 0.5. In a 'reduced' model, right, the same parameter has prior mean zero and standard deviation 1/1000. Bayesian model reduction enables the evidence and parameter(s) of the reduced model to be derived from the evidence and parameter(s) of the full model. |
| Date | |
| Source | Own work |
| Author | Peterzlondon |
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 17:38, 17 May 2018 | | 2,609 × 1,428 (95 KB) | Peterzlondon | Higher resolution version |
| 16:54, 17 May 2018 |  | 514 × 297 (11 KB) | Peterzlondon | User created page with UploadWizard |
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