clustr

A dataframe of alphabetical labels representing
the optimal solution of `traj` dataset based on `akClust`
function

datasets

Advances a novel adaptation of longitudinal k-means clustering
technique (Genolini et al. (2015) <doi:10.18637/jss.v065.i04>)
for grouping trajectories based on the similarities of their
long-term trends and determines the optimal solution based
on either the average silhouette width (Rousseeuw P. J. 1987)
or the Calinski-Harabatz criterion (Calinski and Harabatz (1974)
<doi:10.1080/03610927408827101>). Includes functions to extract
descriptive statistics and generate a visualisation of the
resulting groups, drawing methods from the 'ggplot2' library (Wickham H. (2016)
<doi:10.1007/978-3-319-24277-4>). The package also includes a number of
other useful functions for exploring and manipulating longitudinal
data prior to the clustering process.

Monsuru Adepeju

akmedoids

Anchored Kmedoids for Longitudinal Data Clustering

clustr function

A dataframe containing one variable:<ul>
<li>label: alphabetical label by clusters</li>
</ul>

clustr: Sample labels of cluster groups

Description

Usage

Arguments

Format