Robust Multivariate Methods for High Dimensional Data
Class "CSimca" - classification in high dimensions based on the (cla...
Classification in high dimensions based on the (classical) SIMCA metho...
Accessor methods to the essential slots of Outlier and its subclasse...
Class "Outlier" -- a base class for outlier identification
Class OutlierMahdist - Outlier identification using robust (mahalano...
Outlier identification using robust (mahalanobis) distances based on r...
Class "OutlierPCDist" - Outlier identification in high dimensions us...
Outlier identification in high dimensions using the PCDIST algorithm
Class "OutlierPCOut" - Outlier identification in high dimensions usi...
Outlier identification in high dimensions using the PCOUT algorithm
Class "OutlierSign1" - Outlier identification in high dimensions usi...
Outlier identification in high dimensions using the SIGN1 algorithm
Class "OutlierSign2" - Outlier identification in high dimensions usi...
Outlier identification in high dimensions using the SIGN2 algorithm
Class "PredictSimca" - prediction of "Simca" objects
Class "PredictSosDisc" - prediction of "SosDisc" objects
Class `"RSimca" - robust classification in high dimensions based on th...
Robust classification in high dimensions based on the SIMCA method
Class "Simca" - virtual base class for all classic and robust SIMCA ...
Class "SosDisc" - virtual base class for all classic and robust SosD...
Class SosDiscClassic - sparse multigroup classification by the optim...
Class SosDiscRobust - robust and sparse multigroup classification by...
Robust and sparse multigroup classification by the optimal scoring app...
Class SPcaGrid - Sparse Robust PCA using PP - GRID search Algorithm
Sparse Robust Principal Components based on Projection Pursuit (PP): G...
Class "SummarySimca" - summary of "Simca" objects
Class "SummarySosDisc" - summary of "SosDisc" objects
Robust multivariate methods for high dimensional data including outlier detection (Filzmoser and Todorov (2013) <doi:10.1016/j.ins.2012.10.017>), robust sparse PCA (Croux et al. (2013) <doi:10.1080/00401706.2012.727746>, Todorov and Filzmoser (2013) <doi:10.1007/978-3-642-33042-1_31>), robust PLS (Todorov and Filzmoser (2014) <doi:10.17713/ajs.v43i4.44>), and robust sparse classification (Ortner et al. (2020) <doi:10.1007/s10618-019-00666-8>).