‘kml’ is an implementation of k-means for longitudinal data (or
trajectories). This algorithm is able to deal with missing value
and provides an easy way to re roll the algorithm several times, varying
the starting conditions and/or the number of clusters looked for.
KmL 1.1.1 addition:
- 7 imputations methods for longitudinal data
- Calculus of three qualities criterion (Calinski&Harabatz, Ray&Turi,
Davies&Bouldin)
- Implementation of the Frechet distance between two trajectories
- Calculus of the Frechet path
- Optimization of the function 'dist' for trajectories
- Possibility to use three different ways to define the starting conditions
- Correction of minor bugs
Christophe Genolini
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