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.
Version: 1.4.7 Depends: fake (≥ 1.4.0), R (≥ 3.5) Imports: abind, beepr, future, future.apply, glassoFast (≥ 1.0.0), glmnet, grDevices, igraph, mclust, nloptr, plotrix, Rdpack, withr (≥ 2.4.0) Suggests: cluster, corpcor, dbscan, elasticnet, gglasso, mixOmics, nnet, OpenMx, RCy3, randomcoloR, rCOSA, rmarkdown, rpart, sgPLS, sparcl, survival (≥ 3.2.13), testthat (≥ 3.0.0), visNetwork Published: 2025-04-11 DOI: 10.32614/CRAN.package.sharp Author: Barbara Bodinier [aut, cre] Maintainer: Barbara Bodinier <barbara.bodinier at gmail.com> BugReports: https://github.com/barbarabodinier/sharp/issues License: GPL (≥ 3) URL: https://github.com/barbarabodinier/sharp NeedsCompilation: no Additional_repositories: https://barbarabodinier.github.io/drat Language: en-GB Citation: sharp citation info Materials: README NEWS CRAN checks: sharp results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=sharp to link to this page.
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