Capabilities of R Package mixAK for Clustering Based on Multivariate Continuous and Discrete Longitudinal Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F14%3A10282862" target="_blank" >RIV/00216208:11320/14:10282862 - isvavai.cz</a>
Alternative codes found
RIV/61384399:31160/14:00045373
Result on the web
<a href="http://www.jstatsoft.org/v59/i12/" target="_blank" >http://www.jstatsoft.org/v59/i12/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Capabilities of R Package mixAK for Clustering Based on Multivariate Continuous and Discrete Longitudinal Data
Original language description
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 Komarek and Komarkova (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 give
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GAP403%2F12%2F1557" target="_blank" >GAP403/12/1557: Developing Methods for Identifying and Evaluating Factors That Critically Affect Corporate Performance.</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Statistical Software [online]
ISSN
1548-7660
e-ISSN
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Volume of the periodical
59
Issue of the periodical within the volume
12
Country of publishing house
US - UNITED STATES
Number of pages
38
Pages from-to
1-38
UT code for WoS article
000341807200001
EID of the result in the Scopus database
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