akmedoids: Anchored Kmedoids for Longitudinal Data Clustering

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.

Package details

AuthorMonsuru Adepeju [cre, aut], Samuel Langton [aut], Jon Bannister [aut]
MaintainerMonsuru Adepeju <monsuur2010@yahoo.com>
URL https://cran.r-project.org/package=akmedoids
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the akmedoids package in your browser

Any scripts or data that you put into this service are public.

akmedoids documentation built on April 13, 2021, 9:07 a.m.