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Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Capabilities of R Package mixAK for Clustering Based on Multivariate Continuous and Discrete Longitudinal Data | Komárek | Journal of Statistical Software
Authors: Arnošt Komárek, Lenka Komárková
Title: Capabilities of R Package mixAK for Clustering Based on Multivariate Continuous and Discrete Longitudinal Data
Abstract: R package mixAK originally implemented routines primarily for Bayesian estimation of finite normal mixture models for possibly interval-censored data. The functionality of the package was considerably enhanced by implementing methods for Bayesian estimation of mixtures of multivariate generalized linear mixed models proposed in Komárek and Komárková (2013). Among other things, this allows for a cluster analysis (classification) based on multivariate continuous and discrete longitudinal data that arise whenever multiple outcomes of a different nature are recorded in a longitudinal study. This package also allows for a data-driven selection of a number of clusters as methods for selecting a number of mixture components were implemented. A model and clustering methodology for multivariate continuous and discrete longitudinal data is overviewed. Further, a step-by-step cluster analysis based jointly on three longitudinal variables of different types (continuous, count, dichotomous) is given, which provides a user manual for using the package for similar problems.

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Paper: Capabilities of R Package mixAK for Clustering Based on Multivariate Continuous and Discrete Longitudinal Data     Download PDF (Downloads: 3659)
Supplements:
mixAK_3.8.tar.gz: R source package Download (Downloads: 214; 867KB)
v59i12.R: R example code from the paper Download (Downloads: 266; 35KB)

DOI: 10.18637/jss.v059.i12

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Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.