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| Cars | Consumer reports car data: dimensions |
| CSimca | Classification in high dimensions based on the (classical) SIMCA method |
| CSimca-class | Class '"CSimca"' - classification in high dimensions based on the (classical) SIMCA method |
| CSimca.default | Classification in high dimensions based on the (classical) SIMCA method |
| CSimca.formula | Classification in high dimensions based on the (classical) SIMCA method |
| getClassLabels | Accessor methods to the essential slots of 'Outlier' and its subclasses |
| getClassLabels-method | Class '"Outlier"' - a base class for outlier identification |
| getClassLabels-methods | Accessor methods to the essential slots of 'Outlier' and its subclasses |
| getCutoff | Accessor methods to the essential slots of 'Outlier' and its subclasses |
| getCutoff-method | Class 'OutlierMahdist' - Outlier identification using robust (mahalanobis) distances based on robust multivariate location and covariance matrix |
| getCutoff-method | Class '"OutlierPCDist"' - Outlier identification in high dimensions using using the PCDIST algorithm |
| getCutoff-method | Class '"OutlierPCOut"' - Outlier identification in high dimensions using using the PCOUT algorithm |
| getCutoff-method | Class '"OutlierSign1"' - Outlier identification in high dimensions using the SIGN1 algorithm |
| getCutoff-method | Class '"OutlierSign2"' - Outlier identification in high dimensions using the SIGN2 algorithm |
| getCutoff-methods | Accessor methods to the essential slots of 'Outlier' and its subclasses |
| getDistance-method | Class '"Outlier"' - a base class for outlier identification |
| getDistance-method | Class 'OutlierMahdist' - Outlier identification using robust (mahalanobis) distances based on robust multivariate location and covariance matrix |
| getDistance-method | Class '"OutlierPCDist"' - Outlier identification in high dimensions using using the PCDIST algorithm |
| getDistance-method | Class '"OutlierPCOut"' - Outlier identification in high dimensions using using the PCOUT algorithm |
| getDistance-method | Class '"OutlierSign1"' - Outlier identification in high dimensions using the SIGN1 algorithm |
| getDistance-method | Class '"OutlierSign2"' - Outlier identification in high dimensions using the SIGN2 algorithm |
| getFlag-method | Class '"Outlier"' - a base class for outlier identification |
| getOutliers | Accessor methods to the essential slots of 'Outlier' and its subclasses |
| getOutliers-method | Class '"Outlier"' - a base class for outlier identification |
| getOutliers-methods | Accessor methods to the essential slots of 'Outlier' and its subclasses |
| getQuan-method | Class 'SPcaGrid' - Sparse Robust PCA using PP - GRID search Algorithm |
| getWeight | Accessor methods to the essential slots of 'Outlier' and its subclasses |
| getWeight-method | Class '"Outlier"' - a base class for outlier identification |
| getWeight-methods | Accessor methods to the essential slots of 'Outlier' and its subclasses |
| kibler | 1985 Auto Imports Database |
| kibler.orig | 1985 Auto Imports Database |
| Outlier-class | Class '"Outlier"' - a base class for outlier identification |
| OutlierMahdist | Outlier identification using robust (mahalanobis) distances based on robust multivariate location and covariance matrix |
| OutlierMahdist-class | Class 'OutlierMahdist' - Outlier identification using robust (mahalanobis) distances based on robust multivariate location and covariance matrix |
| OutlierMahdist.default | Outlier identification using robust (mahalanobis) distances based on robust multivariate location and covariance matrix |
| OutlierMahdist.formula | Outlier identification using robust (mahalanobis) distances based on robust multivariate location and covariance matrix |
| OutlierPCDist | Outlier identification in high dimensions using the PCDIST algorithm |
| OutlierPCDist-class | Class '"OutlierPCDist"' - Outlier identification in high dimensions using using the PCDIST algorithm |
| OutlierPCDist.default | Outlier identification in high dimensions using the PCDIST algorithm |
| OutlierPCDist.formula | Outlier identification in high dimensions using the PCDIST algorithm |
| OutlierPCOut | Outlier identification in high dimensions using the PCOUT algorithm |
| OutlierPCOut-class | Class '"OutlierPCOut"' - Outlier identification in high dimensions using using the PCOUT algorithm |
| OutlierPCOut.default | Outlier identification in high dimensions using the PCOUT algorithm |
| OutlierPCOut.formula | Outlier identification in high dimensions using the PCOUT algorithm |
| OutlierSign1 | Outlier identification in high dimensions using the SIGN1 algorithm |
| OutlierSign1-class | Class '"OutlierSign1"' - Outlier identification in high dimensions using the SIGN1 algorithm |
| OutlierSign1.default | Outlier identification in high dimensions using the SIGN1 algorithm |
| OutlierSign1.formula | Outlier identification in high dimensions using the SIGN1 algorithm |
| OutlierSign2 | Outlier identification in high dimensions using the SIGN2 algorithm |
| OutlierSign2-class | Class '"OutlierSign2"' - Outlier identification in high dimensions using the SIGN2 algorithm |
| OutlierSign2.default | Outlier identification in high dimensions using the SIGN2 algorithm |
| OutlierSign2.formula | Outlier identification in high dimensions using the SIGN2 algorithm |
| plot-method | Class '"Outlier"' - a base class for outlier identification |
| plot-method | Class '"OutlierPCOut"' - Outlier identification in high dimensions using using the PCOUT algorithm |
| predict-method | Class '"Simca"' - virtual base class for all classic and robust SIMCA classes representing classification in high dimensions based on the SIMCA method |
| predict-method | Class '"SosDisc"' - virtual base class for all classic and robust SosDisc classes representing the results of the robust and sparse multigroup classification by the optimal scoring approach |
| PredictSimca-class | Class '"PredictSimca"' - prediction of '"Simca"' objects |
| PredictSosDisc-class | Class '"PredictSosDisc"' - prediction of '"SosDisc"' objects |
| rcpp_hello_world | Simple function using Rcpp |
| RSimca | Robust classification in high dimensions based on the SIMCA method |
| RSimca-class | Class '"RSimca" - robust classification in high dimensions based on the SIMCA method' |
| RSimca.default | Robust classification in high dimensions based on the SIMCA method |
| RSimca.formula | Robust classification in high dimensions based on the SIMCA method |
| show-method | Class '"Outlier"' - a base class for outlier identification |
| show-method | Class '"PredictSimca"' - prediction of '"Simca"' objects |
| show-method | Class '"PredictSosDisc"' - prediction of '"SosDisc"' objects |
| show-method | Class '"Simca"' - virtual base class for all classic and robust SIMCA classes representing classification in high dimensions based on the SIMCA method |
| show-method | Class '"SosDisc"' - virtual base class for all classic and robust SosDisc classes representing the results of the robust and sparse multigroup classification by the optimal scoring approach |
| show-method | Class '"SummarySimca"' - summary of '"Simca"' objects |
| show-method | Class '"SummarySosDisc"' - summary of '"SosDisc"' objects |
| Simca-class | Class '"Simca"' - virtual base class for all classic and robust SIMCA classes representing classification in high dimensions based on the SIMCA method |
| SosDisc-class | Class '"SosDisc"' - virtual base class for all classic and robust SosDisc classes representing the results of the robust and sparse multigroup classification by the optimal scoring approach |
| SosDiscClassic-class | Class 'SosDiscClassic' - sparse multigroup classification by the optimal scoring approach |
| SosDiscRobust | Robust and sparse multigroup classification by the optimal scoring approach |
| SosDiscRobust-class | Class 'SosDiscRobust' - robust and sparse multigroup classification by the optimal scoring approach |
| SosDiscRobust.default | Robust and sparse multigroup classification by the optimal scoring approach |
| SosDiscRobust.formula | Robust and sparse multigroup classification by the optimal scoring approach |
| SPcaGrid | Sparse Robust Principal Components based on Projection Pursuit (PP): GRID search Algorithm |
| SPcaGrid-class | Class 'SPcaGrid' - Sparse Robust PCA using PP - GRID search Algorithm |
| SPcaGrid.default | Sparse Robust Principal Components based on Projection Pursuit (PP): GRID search Algorithm |
| SPcaGrid.formula | Sparse Robust Principal Components based on Projection Pursuit (PP): GRID search Algorithm |
| summary-method | Class '"Simca"' - virtual base class for all classic and robust SIMCA classes representing classification in high dimensions based on the SIMCA method |
| summary-method | Class '"SosDisc"' - virtual base class for all classic and robust SosDisc classes representing the results of the robust and sparse multigroup classification by the optimal scoring approach |
| SummarySimca-class | Class '"SummarySimca"' - summary of '"Simca"' objects |
| SummarySosDisc-class | Class '"SummarySosDisc"' - summary of '"SosDisc"' objects |