An implementation of k-means specifically design to cluster joint trajectories (longitudinal data on several variable-trajectories). Like 'kml', it provides facilities to deal with missing value, compute several quality criterion (Calinski and Harabatz, Ray and Turie, Davies and Bouldin, BIC,...) and propose a graphical interface for choosing the 'best' number of clusters. In addition, the 3D graph representing the mean joint-trajectories of each cluster can be exported through LaTeX in a 3D dynamic rotating PDF graph.
[email protected] low health (49/100) — consider alternatives
Get this data programmatically — free, no authentication.
curl https://depscope.dev/api/check/conda/r-kml3dFirst published · 2022-12-14 13:22:46.704000+00:00
Last updated · 2025-09-26 23:14:18.500000+00:00