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  "Date": "2024-01-04",
  "Title": "Clustering Longitudinal Trajectories",
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  "Description": "Clusters longitudinal trajectories over time (can be\nunequally spaced, unequal length time series and/or partially\noverlapping series) on a common time axis. Performs k-means\nclustering on a single continuous variable measured over time,\nwhere each mean is defined by a thin plate spline fit to all\npoints in a cluster. Distance is MSE across trajectory points\nto cluster spline. Provides graphs of derived cluster splines,\nsilhouette plots, and Adjusted Rand Index evaluations of the\nnumber of clusters. Scales well to large data with multicore\nparallelism available to speed computation.",
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