mcca

It contains six common multi-category classification accuracy evaluation measures. All of these measures could be found in Li and Ming (2019) doi:10.1002/sim.8103. Specifically, Hypervolume Under Manifold (HUM), described in Li and Fine (2008) doi:10.1093/biostatistics/kxm050. Correct Classification Percentage (CCP), Integrated Discrimination Improvement (IDI), Net Reclassification Improvement (NRI), R-Squared Value (RSQ), described in Li, Jiang and Fine (2013) doi:10.1093/biostatistics/kxs047. Polytomous Discrimination Index (PDI), described in Van Calster et al. (2012) doi:10.1007/s10654-012-9733-3. Li et al. (2018) doi:10.1177/0962280217692830. We described all these above measures and our mcca package in Li, Gao and D'Agostino (2019) doi:10.1002/sim.8103.

Last 30 days

This package has been downloaded 205 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 2 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 2,798 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 Jan 21, 2025 with 40 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.