| sharp-package | sharp: Stability-enHanced Approaches using Resampling Procedures |
| Adjacency | Stable results |
| AggregatedEffects | Summarised coefficients conditionally on selection |
| Argmax | Calibrated hyper-parameter(s) |
| ArgmaxId | Calibrated hyper-parameter(s) |
| BiSelection | Stability selection of predictors and/or outcomes |
| BlockLambdaGrid | Multi-block grid |
| CalibrationPlot | Calibration plot |
| CART | Classification And Regression Trees |
| Clustering | Consensus clustering |
| ClusteringAlgo | (Weighted) clustering algorithm |
| ClusteringPerformance | Clustering performance |
| Clusters | Stable results |
| Combine | Merging stability selection outputs |
| CoMembership | Pairwise co-membership |
| ConsensusMatrix | Selection/co-membership proportions |
| ConsensusScore | Consensus score |
| DBSCANClustering | (Weighted) density-based clustering |
| Ensemble | Ensemble model |
| EnsemblePredictions | Predictions from ensemble model |
| ExplanatoryPerformance | Prediction performance in regression |
| FDP | False Discovery Proportion |
| Folds | Splitting observations into folds |
| GMMClustering | Model-based clustering |
| Graph | Graph visualisation |
| GraphComparison | Edge-wise comparison of two graphs |
| GraphicalAlgo | Graphical model algorithm |
| GraphicalModel | Stability selection graphical model |
| GroupPLS | Group Partial Least Squares |
| HierarchicalClustering | (Weighted) hierarchical clustering |
| Incremental | Incremental prediction performance in regression |
| IncrementalPlot | Plot of incremental performance |
| KMeansClustering | K-means clustering |
| LambdaGridGraphical | Grid of penalty parameters (graphical model) |
| LambdaGridRegression | Grid of penalty parameters (regression model) |
| LambdaSequence | Sequence of penalty parameters |
| LavaanMatrix | Matrix from lavaan outputs |
| LavaanModel | Writing lavaan model |
| LinearSystemMatrix | Matrix from linear system outputs |
| OpenMxMatrix | Matrix from OpenMx outputs |
| OpenMxModel | Writing OpenMx model (matrix specification) |
| PAMClustering | (Weighted) Partitioning Around Medoids |
| PenalisedGraphical | Graphical LASSO |
| PenalisedLinearSystem | Penalised Structural Equation Model |
| PenalisedOpenMx | Penalised Structural Equation Model |
| PenalisedRegression | Penalised regression |
| PenalisedSEM | Penalised Structural Equation Model |
| PFER | Per Family Error Rate |
| plot.clustering | Consensus matrix heatmap |
| plot.incremental | Plot of incremental performance |
| plot.roc_band | Receiver Operating Characteristic (ROC) band |
| plot.variable_selection | Plot of selection proportions |
| PlotIncremental | Plot of incremental performance |
| PLS | Partial Least Squares 'a la carte' |
| predict.variable_selection | Predict method for stability selection |
| PredictPLS | Partial Least Squares predictions |
| Recalibrate | Regression model refitting |
| Refit | Regression model refitting |
| Resample | Resampling observations |
| SelectedVariables | Stable results |
| SelectionAlgo | Variable selection algorithm |
| SelectionPerformance | Selection performance |
| SelectionPerformanceGraph | Graph representation of selection performance |
| SelectionProportions | Selection/co-membership proportions |
| SparseGroupPLS | Sparse group Partial Least Squares |
| SparsePCA | Sparse Principal Component Analysis |
| SparsePLS | Sparse Partial Least Squares |
| Split | Splitting observations into non-overlapping sets |
| Square | Adjacency from bipartite |
| StabilityMetrics | Stability selection metrics |
| StabilityScore | Stability score |
| Stable | Stable results |
| StructuralModel | Stability selection in Structural Equation Modelling |
| VariableSelection | Stability selection in regression |
| WeightBoxplot | Stable attribute weights |