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 307 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 10 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 3,428 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. 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.