Package: sharp
Type: Package
Title: Stability-enHanced Approaches using Resampling Procedures
Version: 1.4.6
Date: 2024-02-03
Author: Barbara Bodinier [aut, cre]
Maintainer: Barbara Bodinier <barbara.bodinier@gmail.com>
URL: https://github.com/barbarabodinier/sharp
BugReports: https://github.com/barbarabodinier/sharp/issues
Description: 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, 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. 
License: GPL (>= 3)
Language: en-GB
Encoding: UTF-8
RoxygenNote: 7.3.1
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
Additional_repositories: https://barbarabodinier.github.io/drat
Config/testthat/edition: 3
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2024-02-03 16:28:15 UTC; barbara
Repository: CRAN
Date/Publication: 2024-02-03 17:30:02 UTC
Built: R 4.4.0; ; 2024-06-08 03:57:51 UTC; unix
