akmedoids 0.1.2
Anchored Kmedoids for Longitudinal Data Clustering
Released Apr 19, 2019 by Monsuru Adepeju
Dependencies
ggplot2 3.1.1
Hmisc 4.2-0
kml 2.4.1
longitudinalData 2.4.1
reshape2 1.4.3
Advances a novel adaptation of longitudinal k-means clustering technique (Genolini et al. (2015) ) for grouping trajectories based on the similarities of their long-term trends and determines the optimal solution based on the Calinski-Harabatz criterion (Calinski and Harabatz (1974) ). Includes functions to extract descriptive statistics and generate a visualisation of the resulting groups, drawing methods from the 'ggplot2' library (Wickham H. (2016) ). The package also includes a number of other useful functions for exploring and manipulating longitudinal data prior to the clustering process.
