R: Robust Multivariate Methods for High Dimensional Data

# Robust Multivariate Methods for High Dimensional Data

## Documentation for package ‘rrcovHD’ version 0.3-1

- DESCRIPTION file
- Package README

## Help Pages

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
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