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Documentation / Developer's manual

Available modules

Calibration,  DataServer,  Launcher,  MetaModelOptim,  Modeler,  Optimizer,  ReLauncher,  Reliability,  ReOptimizer,  Sampler,  Sensitivity,  UncertModeler,  XmlProblem,   Uranie / Calibration: Class Hierarchy
Uranie / Calibration  v4.11.0
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Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 1234]
 Chide_DistanceLikelihoodConstructor
 CTDoubleEval
 CURANIE::Calibration::TDistanceLikelihoodFunctionDescription of the class TDistanceLikelihoodFunction
 CURANIE::Calibration::TGaussLogLikelihoodFunctionDescription of the class TGaussLogLikelihoodFunction
The log-likelihood is estimated as

\[ \textit{log-}\mathcal{L} \left(\theta | \mathbf{x},\mathbf{y}\right) = -\frac{1}{2}\sum_{j=1}^{n_{Var}}\sum_{i=1}^{n_{Obs}}\left( \log\left( 2 \pi \left(\sigma_i^j\right)^2 \right)+\left(\frac{\mathbf{y^{j}_{i,Obs}} - \mathbf{y^{j}_{i,Est}}}{\sigma_i^j}\right)^2\right) \]

where

 CURANIE::Calibration::TL1DistanceFunctionDescription of the class TL1DistanceFunction
The distance is estimated as

\[ Dist = \sum_{i=1}^{n_{Var}} \alpha_i \times ( \sum_{j=1}^{n_{Obs}} | \mathbf{y^{j}_{i,Obs}} - \mathbf{y^{j}_{i,Est}} | ) \]

where

 CURANIE::Calibration::TLSDistanceFunctionDescription of the class TLSDistanceFunction
The distance is estimated as

\[ Dist = \sum_{i=1}^{n_{Var}} \alpha_i \times \sqrt{ \sum_{j=1}^{n_{Obs}} (\mathbf{y^{j}_{i,Obs}} - \mathbf{y^{j}_{i,Est}})^{2}} \]

where

 CURANIE::Calibration::TMahalanobisDistanceFunctionDescription of the class TMahalanobisDistanceFunction
The distance is estimated as

\[ Dist = \sum_{i=1}^{n_{Var}} \alpha_i \times \sqrt{ (\mathbf{y_{i,Obs}} - \mathbf{y_{i,Est}})^{T} \Omega^{-1} (\mathbf{y_{i,Obs}} - \mathbf{y_{i,Est}}) } \]

where

 CURANIE::Calibration::TRelativeLSDistanceFunctionDescription of the class TRelativeLSDistanceFunction
The distance is estimated as

\[ Dist = \sum_{i=1}^{n_{Var}} \alpha_i \times \sqrt{ \sum_{j=1}^{n_{Obs}} \frac{(\mathbf{y^{j}_{i,Obs}} - \mathbf{y^{j}_{i,Est}})^{2}}{(\mathbf{y^{j}_{i,Obs}})^{2}}} \]

where

 CURANIE::Calibration::TWeightedLSDistanceFunctionDescription of the class TWeightedLSDistanceFunction
The distance is estimated as

\[ Dist = \sum_{i=1}^{n_{Var}} \alpha_i \times \sqrt{ \sum_{j=1}^{n_{Obs}} \beta_{j} (\mathbf{y^{j}_{i,Obs}} - \mathbf{y^{j}_{i,Est}})^{2}} \]

where

 CTNamed
 CURANIE::Calibration::TCalibrationDescription of the class TCalibration
 CURANIE::Calibration::TABC
 CURANIE::Calibration::TPMCABC
 CURANIE::Calibration::TRejectionABC
 CURANIE::Calibration::TLinearBayesianDescription of the class TLinearBayesian
 CURANIE::Calibration::TMCMC
 CURANIE::Calibration::TMinimisationDescription of the class TMinimisation
 CURANIE::Calibration::TUncertModeler
 CURANIE::Calibration::TCirce