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:

Reference manual: clustra.pdf
Vignettes: clustra: clustering trajectories

Downloads:

Package source: clustra_0.1.6.tar.gz
Windows binaries: r-devel: clustra_0.1.6.zip, r-release: clustra_0.1.6.zip, r-oldrel: clustra_0.1.6.zip
macOS binaries: r-release (arm64): clustra_0.1.6.tgz, r-release (x86_64): clustra_0.1.6.tgz, r-oldrel: clustra_0.1.6.tgz
Old sources: clustra archive

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