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- Timestamp:
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Dec 26, 2010, 11:07:40 AM (15 years ago)
- Author:
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Víctor de Buen Remiro
- Comment:
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v16
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v17
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17 | 17 | |
18 | 18 | In order to be estimated with [wiki:OfficialTolArchiveNetworkNonLinGloOpt NonLinGloOpt] |
19 | | (max-likelihood) and [wiki:OfficialTolArchiveNetworkBysSampler BysSampler ] |
| 19 | (max-likelihood) and [wiki:OfficialTolArchiveNetworkBysSampler BysSampler ] |
20 | 20 | (Bayesian sampler), each prior must define methods to calculate the logarithm |
21 | 21 | of the likelihood (except an additive constant), its gradient and its hessian, |
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198 | 198 | For example we can define a log-normal prior without to define explicitly |
199 | 199 | its log-likelihood, gradient and hessian. |
| 200 | |
| 201 | == Composed priors == |
| 202 | If you have a set of priors you can express as just one bye means of |
| 203 | |
| 204 | * adding the log-likelihood functions, the gradients and the hessians, |
| 205 | * concat the set of constraining inequations |
| 206 | * take the maximum of lower bounds |
| 207 | * take the minimum of upper bounds |