briKmeans

Implementation of the BRIk, FABRIk and FDEBRIk algorithms to initialise k-means. These methods are intended for the clustering of multivariate and functional data, respectively. They make use of the Modified Band Depth and bootstrap to identify appropriate initial seeds for k-means, which are proven to be better options than many techniques in the literature. Torrente and Romo (2021) doi:10.1007/s00357-020-09372-3 It makes use of the functions kma and kma.similarity, from the archived package fdakma, by Alice Parodi et al.

Last 30 days

This package has been downloaded 238 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 4 times.

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Last 365 days

This package has been downloaded 2,847 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 Jul 21, 2024 with 70 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.