Package: sharp 1.4.7

sharp: Stability-enHanced Approaches using Resampling Procedures
In stability selection (N Meinshausen, P Bühlmann (2010) <doi:10.1111/j.1467-9868.2010.00740.x>) and consensus clustering (S Monti et al (2003) <doi:10.1023/A:1023949509487>), resampling techniques are used to enhance the reliability of the results. In this package (B Bodinier et al (2025) <doi:10.18637/jss.v112.i05>), hyper-parameters are calibrated by maximising model stability, which is measured under the null hypothesis that all selection (or co-membership) probabilities are identical (B Bodinier et al (2023a) <doi:10.1093/jrsssc/qlad058> and B Bodinier et al (2023b) <doi:10.1093/bioinformatics/btad635>). Functions are readily implemented for the use of LASSO regression, sparse PCA, sparse (group) PLS or graphical LASSO in stability selection, and hierarchical clustering, partitioning around medoids, K means or Gaussian mixture models in consensus clustering.
Authors:
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sharp/json (API)
NEWS
# Install 'sharp' in R: |
install.packages('sharp', repos = c('https://barbarabodinier.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/barbarabodinier/sharp/issues
Last updated 6 days agofrom:61f4ffe4f2. Checks:9 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 27 2025 |
R-4.5-win | OK | Mar 27 2025 |
R-4.5-mac | OK | Mar 27 2025 |
R-4.5-linux | OK | Mar 27 2025 |
R-4.4-win | OK | Mar 27 2025 |
R-4.4-mac | OK | Mar 27 2025 |
R-4.4-linux | OK | Mar 27 2025 |
R-4.3-win | OK | Mar 27 2025 |
R-4.3-mac | OK | Mar 27 2025 |
Exports:AdjacencyAggregatedEffectsArgmaxArgmaxIdBiSelectionBlockLambdaGridCalibrationPlotCARTClusteringClusteringAlgoClusteringPerformanceClustersCombineCoMembershipConsensusMatrixConsensusScoreDBSCANClusteringEnsembleEnsemblePredictionsExplanatoryPerformanceFDPFoldsGMMClusteringGraphGraphComparisonGraphicalAlgoGraphicalModelGroupPLSHierarchicalClusteringIncrementalIncrementalPlotKMeansClusteringLambdaGridGraphicalLambdaGridRegressionLambdaSequenceLinearSystemMatrixOpenMxMatrixOpenMxModelPAMClusteringPenalisedGraphicalPenalisedLinearSystemPenalisedOpenMxPenalisedRegressionPFERPlotIncrementalPLSPredictPLSRecalibrateRefitResampleSelectedVariablesSelectionAlgoSelectionPerformanceSelectionPerformanceGraphSelectionProportionsSparseGroupPLSSparsePCASparsePLSSplitSquareStabilityMetricsStabilityScoreStableStructuralModelVariableSelectionWeightBoxplot
Dependencies:abindaudiobeeprclicodetoolscpp11digestfakeforeachfuturefuture.applyglassoFastglmnetglobalsgluehugeigraphiteratorslatticelifecyclelistenvmagrittrMASSMatrixmclustnloptrparallellypkgconfigplotrixrbibutilsRcppRcppEigenRdpackrlangshapesurvivalvctrswithr