An R package for analyzing and clustering longitudinal data
The akmedoids package advances the clustering of
longitudinal datasets in order to identify clusters of trajectories with
similar long-term linear trends over time, providing an improved cluster
identification as compared with the classic kmeans algorithm. The
package also includes a set of functions for addressing common data
issues, such as missing entries and outliers, prior to conducting
advance longitudinal data analysis. One of the key objectives of this
package is to facilitate easy replication of a recent paper which
examined small area inequality in the crime drop (Adepeju et al.2021).
Many of the functions provided in the akmedoids package may
be applied to longitudinal data in general.
For more information and usability, check out details on CRAN.
For support and bug reports send an email to: monsuur2010@yahoo.com or open an issue here. Code contributions to akmedoids are also very welcome.
Adepeju, M., Langton, S. and Bannister, J. (2021). Anchored k-medoids: a novel adaptation of k-medoids further refined to measure instability in the exposure to crime. Journal of Computational Social Science link