Clusters medical trajectories (unequally spaced and unequal length time series) aligned by an intervention at time 0. Clustering proceeds by an EM algorithm that iterates switching between fitting a bspline to combined responses within each cluster (M-step) and reassigning cluster membership based on nearest fitted bspline (E-step). Initial cluster assignments are random. The fitting is done with the mgcv package function bam, which scales well to very large data sets. Additional parallelism available via multicore on unix and mac platforms.
See the vignette for detailed use examples.