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 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.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: kml, Hmisc, ggplot2, utils, reshape2, longitudinalData
Suggests: knitr, rmarkdown
Published: 2019-03-24
Author: Monsuru Adepeju [cre, aut], Samuel Langton [aut], Jon Bannister [aut]
Maintainer: Monsuru Adepeju <monsuur2010 at yahoo.com>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
CRAN checks: akmedoids results


Reference manual: akmedoids.pdf
Package source: akmedoids_0.1.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
OS X binaries: r-release: not available, r-oldrel: not available


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