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.