sharp: Stability-enHanced Approaches using Resampling Procedures

Implementation of stability selection for graphical modelling and variable selection in regression and dimensionality reduction. These models use on resampling approaches to estimate selection probabilities (N Meinshausen, P Bühlmann (2010) <doi:10.1111/j.1467-9868.2010.00740.x>). Calibration of the hyper-parameters is done via maximisation of a stability score measuring the likelihood of informative (non-uniform) selection (B Bodinier, S Filippi, TH Nost, J Chiquet, M Chadeau-Hyam (2021) <arXiv:2106.02521>).

Version: 1.2.0
Depends: fake
Imports: glassoFast (≥ 1.0.0), glmnet, grDevices, huge, igraph, MASS, mclust, parallel, Rdpack, withr (≥ 2.4.0)
Suggests: cluster, corpcor, dbscan, elasticnet, gglasso, mixOmics, nnet, plotrix, RCy3, rmarkdown, sgPLS, survival (≥ 3.2.13), testthat (≥ 3.0.0), visNetwork
Published: 2022-08-15
Author: Barbara Bodinier [aut, cre]
Maintainer: Barbara Bodinier <b.bodinier at>
License: GPL (≥ 3)
NeedsCompilation: no
Language: en-GB
Materials: README NEWS
CRAN checks: sharp results


Reference manual: sharp.pdf


Package source: sharp_1.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): sharp_1.2.0.tgz, r-oldrel (arm64): sharp_1.2.0.tgz, r-release (x86_64): sharp_1.2.0.tgz, r-oldrel (x86_64): sharp_1.2.0.tgz
Old sources: sharp archive


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