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, 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: |
1.4.6 |
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: |
2024-02-03 |
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 |
Materials: |
README NEWS |
CRAN checks: |
sharp results |
Documentation:
Downloads:
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