kml3d
K-Means for Joint Longitudinal Data
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.
- Version2.5.0
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- kml3d citation info
- Last release10/23/2024
Documentation
Team
Christophe Genolini
Patrice Kiener
Show author detailsRolesContributorBruno Falissard
Show author detailsRolesContributorJean-Baptiste Pingault
Show author detailsRolesContributor
Insights
Last 30 days
This package has been downloaded 699 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 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 7,002 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The day with the most downloads was Mar 28, 2025 with 82 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.
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Dependencies
- Depends5 packages