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- Timestamp:
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Dec 26, 2010, 11:26:06 AM (14 years ago)
- Author:
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Víctor de Buen Remiro
- Comment:
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v18
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v19
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21 | 21 | of the likelihood (except an additive constant), its gradient and its hessian, |
22 | 22 | and an optional set of constraining inequations, in order to define the feasible |
23 | | region. Each inequation can be linear or not and the gradient must |
| 23 | region. Each inequation can be linear or not, but then the gradient must |
24 | 24 | be also calculated. Note that this implies that priors should be continuous and |
25 | 25 | two times differentiable and restrictions must be continuous and differerentiable, |
26 | | but this an admisible restricion in almost all cases. |
| 26 | but this is an admisible restricion in almost all cases. |
| 27 | |
| 28 | In the base class will be the tools to index the subset of variables affected |
| 29 | by prior in the vector of all model variables. |
| 30 | Thus prior methods can be programmed as if there were only them, driving a simple |
| 31 | vector. |
27 | 32 | |
28 | 33 | == Deterministic priors == |
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207 | 212 | * take the maximum of lower bounds |
208 | 213 | * take the minimum of upper bounds |
| 214 | |
| 215 | |