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 by the negative log-likelihood under the null hypothesis that all selection (or co-membership) probabilities are identical (B Bodinier et al (2021) <arXiv:2106.02521>). 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: |
1.3.0 |
| Depends: |
fake (≥ 1.3.0), R (≥ 3.5) |
| Imports: |
beepr, glassoFast (≥ 1.0.0), glmnet, grDevices, huge, igraph, impute, MASS, mclust, parallel, randomcoloR, Rdpack, withr (≥
2.4.0) |
| Suggests: |
cluster, corpcor, dbscan, elasticnet, gglasso, mixOmics, nnet, plotrix, RCy3, rmarkdown, rCOSA, sgPLS, sparcl, survival (≥ 3.2.13), testthat (≥ 3.0.0), visNetwork |
| Published: |
2023-01-17 |
| Author: |
Barbara Bodinier [aut, cre] |
| Maintainer: |
Barbara Bodinier <b.bodinier at imperial.ac.uk> |
| 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 |
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