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CMP++: Uncertainty Quantification & Bayesian Calibration
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This is the complete list of members for cmp::ModelCluster, including all inherited members.
| centroid(size_t i) const | cmp::ModelCluster | inline |
| centroids_ | cmp::ModelCluster | private |
| clusterSize_ | cmp::ModelCluster | private |
| computeProbabilities(const double &T, cmp::classifier::Classifier *classifier, const double &minProb=0.1) const | cmp::ModelCluster | inline |
| computeScore(size_t globalIndex) const | cmp::ModelCluster | inline |
| computeScore(size_t clusterIndex, size_t globalIndex) const | cmp::ModelCluster | inline |
| condition(const Eigen::Ref< const Eigen::MatrixXd > &xObs, const Eigen::Ref< const Eigen::VectorXd > &yObs, const Eigen::Ref< const Eigen::VectorXs > &labels) | cmp::ModelCluster | inline |
| confusionMatrix(std::vector< std::vector< double > > switchingProbability) const | cmp::ModelCluster | inline |
| deterministicSwitchStep(cmp::classifier::Classifier *cls, const size_t &maxAllowedSwitches, const double &minProb) | cmp::ModelCluster | inline |
| dim() const | cmp::ModelCluster | inline |
| dimX_ | cmp::ModelCluster | private |
| fit(Eigen::Ref< const Eigen::VectorXd > lowerBound, Eigen::Ref< const Eigen::VectorXd > upperBound, cmp::gp::method fitType, nlopt::algorithm algorithm=nlopt::LN_SBPLX, double tol=1e-3, std::shared_ptr< cmp::prior::Prior > prior=nullptr, std::vector< bool > logScale={}) | cmp::ModelCluster | inline |
| fit_ | cmp::ModelCluster | private |
| gamma_ | cmp::ModelCluster | private |
| getClusterSize(size_t i) const | cmp::ModelCluster | inline |
| getIndices(size_t clusterIndex) const | cmp::ModelCluster | inline |
| getLabels() const | cmp::ModelCluster | inline |
| getMembership(size_t i) const | cmp::ModelCluster | inline |
| gps_ | cmp::ModelCluster | private |
| kernel_ | cmp::ModelCluster | private |
| labels_ | cmp::ModelCluster | private |
| localIndexTable_ | cmp::ModelCluster | private |
| mean_ | cmp::ModelCluster | private |
| merge(const size_t &clusterIndex1, const size_t &clusterIndex2) | cmp::ModelCluster | inline |
| ModelCluster()=default | cmp::ModelCluster | |
| nClusters() const | cmp::ModelCluster | inline |
| nClusters_ | cmp::ModelCluster | private |
| nObs_ | cmp::ModelCluster | private |
| nPoints() const | cmp::ModelCluster | inline |
| nugget_ | cmp::ModelCluster | private |
| operator[](size_t i) | cmp::ModelCluster | inline |
| parameters_ | cmp::ModelCluster | private |
| performSwitches(const std::vector< std::pair< size_t, size_t > > &newOwners, size_t minSize) | cmp::ModelCluster | inline |
| predict(const Eigen::VectorXd &xStar, cmp::classifier::Classifier *classifier) const | cmp::ModelCluster | inline |
| purge(const size_t &clusterIndex) | cmp::ModelCluster | inline |
| rng_ | cmp::ModelCluster | private |
| set(std::shared_ptr< covariance::Covariance > kernel, std::shared_ptr< mean::Mean > mean, Eigen::VectorXd parameters, double nugget, double gamma, unsigned int seed) | cmp::ModelCluster | inline |
| switchStep(cmp::classifier::Classifier *classifier, size_t maxAllowedSwitches=10, double minProb=0.1, double T=1.0) | cmp::ModelCluster | inline |
| updateModel(const std::vector< bool > &affectedClusters) | cmp::ModelCluster | inline |
| xObs_ | cmp::ModelCluster | private |
| yObs_ | cmp::ModelCluster | private |