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traj

The goal of traj is to implement a three-step procedure in the spirit of Leffondre et al. (2004) to identify clusters of individual longitudinal trajectories. The procedure involves (1) computing a number of “measures of change” capturing various features of the trajectories; (2) using a Principal Component Analysis based dimension reduction algorithm to select a subset of measures and (3) using the k-medoids or k-means algorithm to identify clusters of trajectories.

Installation

You can install the development version of traj from GitHub with:

# install.packages("devtools")
devtools::install_github("IcatianTrout/traj")

Example

See the vignette.

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Version

Install

install.packages('traj')

Monthly Downloads

550

Version

2.2.1

License

MIT + file LICENSE

Maintainer

Laurence Boulanger

Last Published

February 1st, 2025

Functions in traj (2.2.1)

trajdata

trajdata
Step2Selection

Select a Subset of the Measures Using Factor Analysis
Step1Measures

Compute Measures for Identifying Patterns of Change in Longitudinal Data
Step3Clusters

Classify the Longitudinal Data Based on the Selected Measures.
plot.trajClusters

Plots trajClusters objects
traj-package

traj: Clustering of Functional Data Based on Measures of Change