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>). This package also includes tools to simulate multivariate Normal data with different (partial) correlation structures.
| Version: |
1.1.0 |
| 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: |
2022-06-17 |
| 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 |
| Language: |
en-GB |
| Materials: |
README NEWS |
| CRAN checks: |
sharp results |
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