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CMP++: Uncertainty Quantification & Bayesian Calibration
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Base class for prior probability distributions. More...
#include <prior++.h>

Public Member Functions | |
| virtual | ~Prior ()=default |
| virtual double | eval (const Eigen::VectorXd &par) const =0 |
| virtual double | evalGradient (const Eigen::VectorXd &par, const size_t &i) const =0 |
| virtual double | evalHessian (const Eigen::VectorXd &par, const size_t &i, const size_t &j) const =0 |
Base class for prior probability distributions.
Mathematical Formulation Represents a log-prior probability density function \( \log p(\theta) \) over parameters \( \theta \in \mathbb{R}^d \). Provides virtual interfaces for evaluation, gradient, and Hessian computation:
Hessian: \( \mathcal{H}_{ij} f(\theta) = \frac{\partial^2 \log p(\theta)}{\partial \theta_i \partial \theta_j} \)
Implementation Algorithm Pure virtual interface specifying the contract for prior evaluation. Concrete subclasses must implement eval, evalGradient, and evalHessian.
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virtualdefault |
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pure virtual |
Implemented in cmp::prior::Product, cmp::prior::Uniform, and cmp::prior::FromDistribution< DistType >.
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pure virtual |
Implemented in cmp::prior::Product, cmp::prior::Uniform, and cmp::prior::FromDistribution< DistType >.
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pure virtual |
Implemented in cmp::prior::Product, cmp::prior::Uniform, and cmp::prior::FromDistribution< DistType >.