sharp

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.

Last 30 days

This package has been downloaded 341 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 3,433 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Aug 01, 2024 with 42 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.