clustra: Clustering Longitudinal Trajectories
Clusters longitudinal trajectories over time (can be unequally
spaced, unequal length time series and/or partially overlapping series) on
a common time axis. Performs k-means clustering on a single continuous
variable measured over time, where each mean is defined by a thin plate
spline fit to all points in a cluster. Distance is MSE across trajectory
points to cluster spline. Provides graphs of derived cluster splines,
silhouette plots, and Adjusted Rand Index evaluations of the number
of clusters. Scales well to large data with multicore parallelism available
to speed computation.
| Version: |
0.1.6 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
data.table, graphics, grDevices, methods, mgcv, MixSim, parallel, stats |
| Suggests: |
ggplot2, knitr, rmarkdown |
| Published: |
2022-01-16 |
| Author: |
George Ostrouchov [aut, cre],
David Gagnon [aut],
Hanna Gerlovin [aut],
Chen Wei-Chen [ctb],
Schmidt Drew [ctb],
Oak Ridge National Laboratory [cph],
U.S. Department of Veteran's Affairs [fnd] (Project: Million Veteran
Program Data Core) |
| Maintainer: |
George Ostrouchov <ostrouchovg at ornl.gov> |
| License: |
BSD 2-clause License + file LICENSE |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
clustra results |
Documentation:
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