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distances for classification", "topics": [ "calculate_mahalanobis_distances" ] }, { "page": "calculate_prediction_probabilities", "title": "Calculate prediction probabilities from distances", "topics": [ "calculate_prediction_probabilities" ] }, { "page": "compare_models", "title": "Compare multiple O2PLS models", "topics": [ "compare_models" ] }, { "page": "loadings", "title": "Extract the loadings from an O2PLS fit", "topics": [ "loadings", "loadings.O2pls" ] }, { "page": "loadings.o2plsda", "title": "extract the loading value from the O2PLSDA analysis", "topics": [ "loadings.o2plsda" ] }, { "page": "loadings.plsda", "title": "extract the loading value from the PLSDA analysis", "topics": [ "loadings.plsda" ] }, { "page": "o2cv", "title": "Cross validation for O2PLS", "topics": [ "o2cv" ] }, { "page": "o2cv_sparse", "title": "Enhanced sparse cross-validation that integrates with existing o2cv", "topics": [ "o2cv_sparse" ] }, { "page": "o2pls", "title": "fit O2PLS model with best nc, nx, ny", "topics": [ "o2pls" ] }, { "page": "O2pls-class", "title": "Class \"O2pls\" This class represents the Annotation information", "topics": [ "O2pls-class" ] }, { "page": "oplsda", "title": "Orthogonal partial least squares discriminant analysis", "topics": [ "oplsda" ] }, { "page": "plot.O2pls", "title": "Score or loading plot for the O2PLS results", "topics": [ "plot.O2pls" ] }, { "page": "plot.o2plsda", "title": "Score, VIP or loading plot for the O2PLS results", "topics": [ "plot.o2plsda" ] }, { "page": "plot.plsda", "title": "Score, VIP or loading plot for the plsda results", "topics": [ "plot.plsda" ] }, { "page": "plot.sparse_plsda", "title": "Plot method for Sparse PLS-DA results", "topics": [ "plot.sparse_plsda" ] }, { "page": "plot.SparseO2pls", "title": "Plot method for SparseO2pls S4 objects", "topics": [ "plot.SparseO2pls" ] }, { "page": "plot.stability_selection", "title": "Enhanced plot method for stability_selection objects", "topics": [ "plot.stability_selection" ] }, { "page": "plot.TuneResult", "title": "Enhanced plot method for TuneResult objects", "topics": [ "plot.TuneResult" ] }, { "page": "plsda", "title": "Partial least squares discriminant analysis", "topics": [ "plsda" ] }, { "page": "predict-sparse_plsda", "title": "Predict method for sparse_plsda objects", "topics": [ "predict,sparse_plsda-method" ] }, { "page": "predict-SparseO2pls", "title": "Predict method for SparseO2pls objects", "topics": [ "predict,SparseO2pls-method" ] }, { "page": "predict.sparse_plsda", "title": "Enhanced predict method for sparse PLS-DA", "topics": [ "predict.sparse_plsda" ] }, { "page": "predict.SparseO2pls", "title": "Enhanced predict method for sparse O2PLS", "topics": [ "predict.SparseO2pls" ] }, { "page": "print.O2pls", "title": "Print the summary of O2PLS results.", "topics": [ "print.O2pls" ] }, { "page": "print.plsda", "title": "Print the summary of plsda results.", "topics": [ "print.plsda" ] }, { "page": "print.SparseO2pls", "title": "Print method for sparse O2PLS results", "topics": [ "print.SparseO2pls" ] }, { "page": "scad_threshold", "title": "Enhanced SCAD thresholding function", "topics": [ "scad_threshold" ] }, { "page": "scores", "title": "Extract the scores from an O2PLS fit", "topics": [ "scores" ] }, { "page": "scores.O2pls", "title": "Extract the scores from an O2PLS fit", "topics": [ "scores.O2pls" ] }, { "page": "scores.o2plsda", "title": "Extract the scores from an O2PLS DA analysis", "topics": [ "scores.o2plsda" ] }, { "page": "scores.plsda", "title": "Extract the scores PLSDA analysis", "topics": [ "scores.plsda" ] }, { "page": "selected_var_names", "title": "Get names of selected variables", "topics": [ "selected_var_names" ] }, { "page": "selected_vars", "title": "Extract selected variables from sparse models", "topics": [ "selected_vars" ] }, { "page": "selected_vars.default", "title": "Default method for selected_vars", "topics": [ "selected_vars.default" ] }, { "page": "selected_vars.sparse_plsda", 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